{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NLP\n",
    "\n",
    "语言处理、语音识别等方面，文档中每句话的长度是不一样的，且一句话的前后是有关系的，类似这样的数据还有很多，如语音数据、翻译的语句等。像这样与先后顺序有关的数据被称之为**序列数据**。\n",
    "\n",
    "对于序列数据，可以使用循环神经网络（Recurrent NaturalNetwork，RNN），它特别适合处理序列数据，RNN是一种常用的神经网络结构，已经成功应用于自然语言处理（Neuro-Linguistic Programming，NLP）、语音识别、图片标注、机器翻译等众多时序问题中。"
   ]
  },
  {
   "attachments": {
    "3fadf6f8-46d7-4968-a10b-c3f4d28324c5.png": {
     "image/png": 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ai4+WpkuX8ls5ShcCRlYhtqdKRXRiJCoM6kuWLHHPPfecdHrcE3AD4LoSW4jFKVLWEKiSkEpPEFb37t3dCSecIF7vfJ/QgiEQNgJGViEirNISHR6ywp+KLyTjIc4Xkpnnh1e6Xk83yYryU+74AHmxvAze9cwdfPzxx6VueaWNv9fODYGiImBkVVTkCnEfnR57FNNXRo8eLcb03r17Sw50fEhKDdyFyDb0pEh7bJQ/KP2pxNimTRuZr7h+/Xr35ptvijoYeqHsARmLgJFViE2vRERnZ4UDJiezrtTgwYNlcnBw1I+06RiUsLRsWk7KTjjqqKPcwQcfLMvXoOJibId8VUpE9bVgCCQDASOrZKBYQB50dqQqpI8vvvhC1oxiLSp1U9DOX0AWJX4pvoycaxzuDANPGCijgnwRGpKCnNk4Jh3HFgyB4iJgZFVcBAu4Xzs0nfXDDz90K1eulCVXmJgc5aBkhOqKO8NRRx8lPlhfffWVrNqANKV1V5UxyvW1sqcHAkZWIbYDkoUa1lm9AKN069atZSQwxMeGnjVEpGoehMWIJjY4puQsXrxYnk8aJSzdh14we0CpRsDIKsTmhajYmKbCuuesk96oUSNRC0N8bEqyRmKCsFRy6tKli9ircHRFslIysxHClDRHRjzEyCrEZqYjMwl4+vTp0qk7deokUlXUJQ3UQOoAIXGMsR0SZqG+CRMmxMiK61Gva4ivh2VdSASMrAoJWGGSK1mxBAy2nXbt2pWKzqtuFhARdcRJtE6dOiI5MiK4evXqmIGd6yplFQY7S2sIxCNgZBWPSBLP6aQsE7xs2TLXuHFjMUIjiZSWAFkpYfHhigMPPFCIiS/n6BIz1NWkq9LS4iVbDyOrkPHnQ6QrVqxwOFAiXZXmAFkx0skaXai/GoysFAnbFwcBI6vioJfAvXRa1KKmTZvGVlVI4LZIJsHnCv8xJEmVIE0FjGRTpmWhjaxCbBY6KuuYs3TxQQcdVOolK+xWuDEgSaqvFVKVEVaIL1kGZW1kFWJj01FZOgXCYglgDNOlOeCpz4Y0CUEpSem+NNfd6hY+AkZWIWKsUkWw44b4uBLPGjJmEUHIio+mKkmZzarEm6ZUFMDIKsRm1M7KI9Q3KcTHlXjWuCnwIVQkSeZCWjAEkomAkVUy0Swgr0yQLiBnpCokLF1RogBI7JIhUCgEyhcqtSUuNAJ0YHWiLPTNEbuBqTWMfDIiyKJ8mUDQEWuiSBfXJKuQm48Oi5SBDQdVMKgahvzolGdP3agn/mQQFoG40lznlIOcwQ80sgqx8SEqli1mOJ9PbwW9ukN8bIllzVd7kK6QqnTk04iqxJqj1D3YyCrEJkWSYhoKS8PgKIkbQ2kIQQJSyYk9dWSdeTzZIStNZ+pgaWj1kq+DkVXIbQBR7bfffvLZdYzPpSUoEWl9OGdxQT7LxeoLQbKyZWIUJdsXBwEjq+Kgt5d7kSggKzovH4vAkz2+k+8li7S8TL3YdL11JEg2VF0kqxYtWojdStPh0mDBECguAvYWFRfBvdyP/YZ5gXwogs5cWgLkBBkRkJwgYhYYRIpkbSuuKTFrutJSd6tHySBgZBUy7kw/4fuAqICsUV4aOi4kBFmpER0IUQFZYaJt27YiVQWvKWmFDLVlX8oRMLIKuYFZmI4OzCTfWbNmSaeOug0HwkW1g7AITFqeO3euYzTwyCOPFBLTRfdIWxoIOuTXxLJPAAEjqwRAKmoSSIlOi/sCa5T/9NNPYmjPa1RQO35Rn5XK+5CUICDKTB2ZWjNt2jQhZF0NlWukIa1JVqlsndL7LCOrENsWFRB1iH3fvn2FuCZPnhz71Lp2ZPZ07ih1aiVipKoff/zRffTRR65Vq1bugAMOiK0zbxJViC9XBmZtZBVio6u0BAkxQoY6+P7778uUlKAqGDWigqCQGJEQcVUYOXKk2Kn4IAZ+ZVo3yEq3EGG2rDMEASOrEBta7TY8guV+e/ToIYb2Dz74QOw7DP1riJIUgqQIYSE18hXmqVOnuu7duwsZUx/qrfVR6VHraXtDoKgIGFkVFbkE7lOJiY5LBz7kkEPEdsUHT+nkQTKLkgQCUVE33BX40jSG9dNPP10WGKROkBj1UaKKknqbQLNakhJCwMgqZOC189KB69at604++WTp3G+++aZ8/JSOT4hSh0aygqymTJkiI5y/+tWvZNlm4jVofaJEwlp226cnAkZWIbYLREVQGw+rLxx++OGuT58+MiqIVMIqBWqs1g7OPXqse+JKIqh0SDnYOMdnDAfQUaNGyQggUhWTtSEmDZqW85Kug5bJ9tFGwMgq5PajA+NrxR6yYvmUc8891zVp0sQ9/fTTbsGCBVICSECJAfKig7MnrqSCqns8n2PKg52ND0I888wzju8DDhgwQDzWkRwJSlgqUXKupC0J7I8hUEQEjKyKCFxRb6Pzog6eeeaZQlz//ve/3eLFi4WUuKYSCXs9LynJBAJi4/moeOyxU73xxhvunXfeEZW2V69eUk7KasEQCBMBI6sw0c0jbzo1EhbOkxDWqlWrnBLW5s2bRXqBIFSSKUmpBHJioyy4KVC+MWPGuLfeessdddRR7rTTTpMPRGgZdZ9HtS3KECg2AkZWxYaw8BkgpTDBGVvPiSeeKEbqu+66S+xAqH2oWhAaxAZRlFTQsqD+YVt799133ZNPPikTs4cNG+bq168v5VQJrKTKac/NDATK/dmHzKhq+tQSAzWEBRk18bYrOju+V8uXLxf7D2oiREE80kpJSSxKlKh+GNOfeuop17x5c3fJJZe4Zs2aCVFRNsiVPfWxYAiEhcCeseawnmD55kIAgzvqFZ0bYjrllFOkw7/66qsSP3jwYHGwZIQt6A6QK6MiRPBcAs/WYz2XC/6PxkNWzGccO3asw9WCqTQjRowQyYo11jUPpEDSsrdgCISFQBn/Yma/vWE9wfLNhUBekKNqoWK9/PLLYrcaPny4O/bYY2XxPpWsuE+lFz0Onmtcrgf+EoG0xkZ+bKRnI+j5L0mFfKZPn+5eeOEF9/HHH8uo34UXXij+VCrxaVrbGwKpQMDIKhUoxz1DCSIYTRzqFp7tzz//vPv+++9Fujr77LNlz3QdlWRQu5C4IBglK/LKK9/4Z3CuhKX5EYcBHYmPlT6Z78eI39tvvy15HnfccY6NFU95LmQVfC73WzAEwkbAyCpshPPIPz9SQbpixA3bFT5Yn3/+uSwvM3ToUHfwwQe7/fffX85Rt0jLHsIiaJ4QEUSSH5kECUrv4wvK5MdSL/Pnzxf71MyZM8U+hYras2dPITLITPPX58rD7Y8hkAIEjKxSAHL8I5RY4uM5x/YDIbBNmjTJYcf69NNPRarp3bu3uAy0bNlS1EMlDvLjGImnoEA6JTHScw7p4Jg6Y8YMN378eJHsatSo4QYNGuR4nn6phvu4h8A9RlYFIW3XwkDAyCoMVPeSZ35khXQDCTBaCDmgmuEtjkqISjZ79mxxJG3YsKFjOZbDDjvM1atXTz4oitTDxn26xRcDCYo82dasWSP5ffbpZ27hooVyjgGddbc6d+4sbgmonvFGc8pI/sk2/MeX1c4NgXgEjKziEUnBeX5kpfG61xE2yIuVDSCr0aNHy1ruSDkQCcTVunVrcSXgQw18TSdoUyIv0rItWbJEpsiwvPJ3330ntimuIz2h6jFnkePgPD91SyBPygNRBfNPAVz2CENAEDCyisCLoGRDUZFs+EoONqVvv/1WSAcSwhMeAz1kUrNmzZjkA8Hg0MnGwni1atUSqQmSY0FAllvGZ0oN+PlJZRGAyYpYyhEwsopIA6u0BXFBQEg8qHN8UQaVjmMdyVu9erWkoWpIX5AU68Drp+yxSUFonKPOoT6aWheRFyGDi2lkFYHGh6CQeFSlY49tizgNeh3JCzILpmWlB0iLOL2HPfkSONZ4zc/2hkC6IWBklW4tkkB5IBklHkiLY0iKwDlkhaQEAWk6rnGseyU7jTOyEmjsTxojYGSVxo2jRVNC4Tx4zLkSVyJGb+5VAuNePWZvZAUiFtIZASOrdG6dX8qm6hqneZFK1m5PQmX3SFGkx37FKCL2KlTA4H0qhSVCcBGAx4qYIQjYEjERaGhUNt1UCpK98zYrT1RZnpx27/J2Lc69prd923Y3bern7h+33e5WLP9R4rxIxlUhLVREVRMjUH0roiEgCNiqC5F+EbJ9qMriue7JCNLybOS+9x7pDz74oEyd6datm6yTXtmv4OA5L4eEFemqW+EzDgGTrCLc5NjLkbiEqHw9UP12eBcGlnP56quv3IqfVrjXXntN3BuybV17Rg8jXG0reoYiYGQV5YbP1vqkBtAQNihWbeCrz0ytgcimz8he5mWXHyEUPTDK9bWyZzQCRlYRb/7dv7gs7PZi1lrvwf7666/LfEKM6EhTO7bvkOWIv/76ayGwiFfXip/BCBhZRbnxvXG9nDeWE1D/5vi5g++8+47buGmjt7PjU1VGRgRZcubN0W+6dWvXCYHFuz9IBvbHEEhzBIys0ryBCiyeN6ZL8HtWZ3ju+ef8HMHV2Q6inqu4yqihfOzhnXdFRdRVF1TyMuIqEGG7mEYIGFmlUWMUtigQESOAO/08QZaQ+WLaF9lZQFT+mjqMImUt/3G5rNjAXEKuEYyosuGyv9FAwMgqGu2UZymRjphaw6oL48aNkwnN2LCwX4ka6Dlpd1a2/xWOo598MtmN9wvsQWI6fxDCCjqd5vkgizQE0gABI6s0aISiFoHRvw1+vXSM6ouXLJaVF8R51EtO/CtbNnvl0F27s+cNrl27Vj5KgQ2LQFqTroqKvt2XagSMrFKNeBKfh/1p3rx5IlVhPId8RKry0pJITl6CKlvGe7/7DVJiWZmVK1e6l156SdZbRx3ULYnFsqwMgVAQMLIKBdbUZLrN+1KNH/+hW7x4sUyf0e8MsmdZGMiL0cLK+1R2++zr4/y3/pgviCq4cOHC2Mig2rBSU2p7iiFQNARsuk3RcEuLu76dP8/9+OOPrmPnTkJMFAoJCkJiQb6V/gOlzfxXcZjMLIqhn+ysqh92LtZxR5XkHiOstGhSK0QBCNiqCwWAk+6XsEHhqa4qnq72yee8nnjiCflizU033STLF5OGAClhmIfAWMoY8iKOvQVDIJ0RMMkqnVtnL2WrVq2afCAC8oFwdMkX7FKstc7SMCxhzPcGlazIUqUpzd6kKkXC9umMgJFVOrfOXsqGNKRfZ1YyYo+EBYHhkgAREafqH+fqqqB7Jbm9PM4uGwIlioDJ/iUKf/EeriSkhMQ5GyQEOUFCHKtPlZIT6dniJazilcbuNgTCRcDIKlx8Q89dbU0QjwbiICYlJL5eEyQ20kFgBL1fTuyPIZDGCJgamMaNs7eixRMN5ERQklJJKp6ouI49ixAkOYmwP4ZAmiJgklWaNowVyxAwBHIiYGSVEw87MwQMgTRFwMgqTRvGimUIGAI5ETCyyomHnRkChkCaImBklaYNY8UyBAyBnAgYWeXEw84MAUMgTREwskrThrFiGQKGQE4EjKxy4mFnhoAhkKYIGFmlacNYsQwBQyAnAkZWOfGwM0PAEEhTBIys0rRhrFiGgCGQEwEjq5x42JkhYAikKQJGVmnaMFYsQ8AQyImAkVVOPOzMEDAE0hQBI6s0bRgrliFgCOREwMgqJx52ZggYAmmKgJFVmjaMFcsQMARyImBklRMPOzMEDIE0RcDIKk0bxoplCBgCOREwssqJh50ZAoZAmiJgZJWmDWPFMgQMgZwIGFnlxMPODAFDIE0RMLJK04axYhkChkBOBIyscuKR9DO+2Ufgc+56zF6/ksyxbqTRwGfhNV7jbG8IZDICRlYhtj5kox8e1Q+S6odHiedYv4xMMYhTgipfvrwcK2mFWEzL2hCIBAL2ReYQmwlJKfjFY4iIACkRr2QWJDDIS4mMNHw5mXMLhkCmI2BkFeIboNIUZANxbdu2LQdJKXkhRQUJKagiQmQVK1bMQXohFtmyNgTSFgEjqxCbRgkIUoJ0li1b5n7++ecYMRG3zz77uObNm7vKlStLSbi+eNFiiV+7bq2rVq2aa926tZyHWFTL2hBIewSMrEJsIpWceMSmTZvcDz/84N5//303evRoIay+ffu6Xr16uf3331/ICPJavny5e/a5Z92kSZNcy5Yt3SmnnOKaNm1qZBViO1nW0UDAyCrEdkKyUsKqWrWq69y5s5yPGzdOJKb+/ftLHNIT6Ui/3377uVq1arnu3bu7888/X6SqKlWqhFhKy9oQiAYCRlYhtpOqgTwCY3mlSpXcvvvuK8e1a9d2DRs2FNJCosJutW7dOrd69WpRFa+44gq5DlEF8wmxuJa1IZDWCBhZhdw8QekKUlqzZo3YryCn6tWrO4zwjPht375dyAo18fjjjxeiwp6lRvqQi2nZGwJpj4D5WYXYRKh2qgZCWkpW+E4hYUFWxHMOWaEeEt+1a1cZAaRoen+IxbSsDYFIIGBkFWIzQU4EJRzcF1DzCEhNqIW4M0BWEyZMkNHCE044wdWsWVNcHUgXdBrl3IIhkKkIGFmF2PJBFQ7Cgqw2btwoNis1mpPm+++/F7I6++yzXb169UQtxLeKgLpowRAwBHxfMBBShwASFEZ0Qp06dWS/fv1699FHH4nqh8FdPdbV892M6wKT/TEEnElWKXgJkKrUNgU5ITXhnoCk9d5774m9qmfPnqIaKjmx1+MUFNEeYQikPQJGVilqIghr69atbsOGDfJEJKjp06e7WbNmObVTqTSVoiLZYwyBSCFgZBVyc6lUhZQEWeHJThyjf6h/p556qqtfv76UwiSpkBvDso80AkZWITZfkKh4DCN/kBXq3+zZs13jxo1dgwYNxF0hxGJY1oZAqUDAyCrEZgxKShDXli1bHDYr3BEqV6rsevfu7fBkh7yCI4chFsmyNgQii4CNBqao6VABkawgrDZt2rjTTj/N1a1bV0gKUlMpLEXFsccYApFDwCSrEJtMnUJ5BP5SEBUTmocNG+batWsnRGUSVYgNYFmXKgRMsgqxOZGWlLCQnnBXGDJkiOvUqVNs/SquG2GF2AiWdalBwMgqxKbEFUHJSNW/Ro0aiXTFYyGwoF0rxKJY1oZA5BEwsgqxCZWMkLBwBGU1UF1pgWsQmZFViA1gWZcqBMxmlYLmZLQPKQvSUsdPjlX945g0FgwBQyB/BEyyyh+bpFxBctLJyJCTSlIQFMdKWhqflIdaJoZAKUTAyCrkRs2LhIjT+Ph9yMWx7A2ByCJgamBkm84KbghkFgJGVpnV3lZbQyCyCBhZRbbprOCGQGYhYGSVWe1ttTUEIouAkVVkm84KbghkFgJGVpnV3lZbQyCyCBhZRbbprOCGQGYhYGSVWe1ttTUEIouAkVVkm84KbghkFgJGVpnV3lZbQyCyCBhZRbbprOCGQGYhYGSVWe1ttTUEIouAkVVkm84KbghkFgJGVpnV3lZbQyCyCBhZRbbprOCGQGYhYGSVWe1ttTUEIouAkVVkm84KbghkFgJGVpnV3lZbQyCyCBhZRbbprOCGQGYhYGSVWe1ttTUEIouAkVVkm84KbghkFgJGVpnV3lZbQyCyCNinuCLbdFbwdEGAL2vz/ce8Ap9aC17T70USz3ck87o3+H3JvPLM1Dgjq0xteat3sRGAeNjWrVvntm/fLsd80Hbnzp3yXcjKlSu7bdu2ybGSEukrVqjoKlaq6KpWreo2bdrktmzZIsTFfRUrVnTVqlWLfRhXvytZ7MKWggyMrEpBI1oVSg4BSGjOnDlu0qRJ7ssvvxSSqVu3rjviiCNcly5d3DfffOOmT5/u5s2bJ1LU/vvv7zp37uzatWvnmjVr5qZMmeLGjh3r1q5d6w488EB35JFHul69erly5coJ+bG3kI2A2azsTTAEioEAZNW6desYMc2YMcO1aNHCHX300a5GjRrusMMOcx06dHBLlixxEyZMcLVq1RKyatKkiatQoYJr2bKlENyPP/4o6Q4//HBXqVKlHKpjMYpXqm41yapUNadVJpUIoKJBOKhz9erVE4KBjHr27CmqHFIRaiGSFsfVq1d3bdq0EQkKdQ+VEDUQNXL48OFyH2mIJ29TAXO2pklWOfGwM0OgUAgosbDH9gTZ7LvvvrE8Nm/e7N577z23fPlyIa5GjRoJwZEAe9bXX3/tkLIgOCQxjOsQGxIbm4U9CJhktQcLOzIECo2ASkAQz65du4SskLYgHeIWL17sJk6cKNIShAYhkY7jRYsWuW+//dZdeOGFrmbNmkJmFIBrFnIjYJJVbkwsxhAoFAJIQGvWrHE7duxwtWvXFskI6Wjp0qXu6aefdt26dXP77LOPjPShEkJk69evd2+99ZZc22+//eQefagSoKmBikj23iSrnHjYmSGQMAJIQGyQ1IoVK+Q+yAo7FSrhRx995Bo3buzq1Kkj9idURKQu7FRfffWVqHmHHHKIkJcR095hN8lq7xhZCkMgTwRUAsLHitE8ziErCAwyWr16tRswYEBM7UOC4tpPP/3kXnjhBTdw4EAZHTSiyhPeXJFGVrkgsQhDoHAI4My5cuVKISJGBZGqxo0bJz5TSFWcEyAyRv7eeecdd+yxx4qfFVIYaqGFvSNgauDeMbIUhkCBCGCzgqywUyE5ff755+6AAw5wzZs3F2kLSQpSgrjwtcKPql+/fkJSxFtIDAGj9MRwslSGQL4IIFmh8kE8q1atEsnpxBNPFF8rRv4gK+xa2KzwWMfxk1FBfK0sJI6AkVXiWFlKQyAXAkhS2KwgKcgHFe+kk04SJ1HmBkJSEBn+VtOmTRNv94MPPljsWOZLlQvOAiOMrAqExy4aAgUjgHEcMkK6Yuvatas79NBDYz5TxG3cuFHUQWxTqH9VqlSRUUE10JvzZ8EY61VTmBUJ2xsCRUQAHytCq1at3HHHHSe2KTWas0fqwrh+ySWXiMSlJIVUZiOBiYNuklXiWFlKQyAHApANNinIiik2Z555pmvatKkQkHqpowZyfOqpp8pKC/hZsRGIJyixyYn9yRcBI6t8obELhkDBCCAVQTRMq8FoztIu2KmIh8ggKlQ8HD/79u0r1zjnGnvuVcIr+El2FQRMDbT3wBAoIgJKOgcddJAsEcNaVarWQURITqzIwNw/1qpCouIeNq6rrYpjC3tHwMhq7xhZCkMgTwQgJtwVunfvLteDpIPPFef4W+kSMaRXMuMG0lhIHAEjq8SxspSGQJ4I5OfYqeQUJLE8M7DIhBAw+TMhmCyRIWAIlDQCRlYl3QL2fEPAEEgIASOrhGCyRIaAIVDSCJjNqqRbwJ5fJASCLgA6KseeoCNu+WWsRm722JOCtiU91jT55WHxqUfAyCr1mNsT80EAAlKyIAlD/0oaHCuxQEYsYMe2YcMGWUuKT16x8gHLCPNZK3yfWGOK+5S8cB1g5QMmFDPlha/QNGjQwLEuev369WXiMd/sY1VPjOZKfpRFyZERPPLkXJ07KSNptYxcy8/oTl4WioaAkVXRcLO7koCAkghZ0eEhI+KUGIhXx0rm17F6AR9egIQ45vNWP/zwg5AWBMPG8isscgeRtG3bNkY65E++TChm4jHEMmvWLPfFF1/IM7iX+xo2bCgbflEQGXEQD+Sm5WMf73ZA/hrHdQvJR8DIKvmYWo6FQEAlEjo6G+dM/lXSYuE6Pqrw/vvvu7lz54rk9PPPP4sUxHpRrG/exH8dBl8mprzw4QUcMSEYjslTyQOCgvS2bt0qkhdz9pDMWBDvu+++k+ewLjpxLOGCsyfe5zyDT2hBhKysoKSlEhXV5Zig5dZnSqT9SQoCRlZJgdEyKSoCdGrt/JAJnZ2PKSxYsMBNnjzZffzxxyJBQUCsZ878O75ajLMlRIQEFSQkPYY8ght5I1mRDxvPYVVPpCzSHXPMMbKiJ2mQ3PgiDc9//fXX3ahRo2T54UGDBrkePXqI5KXf/eN55M1en2dEVdS3oeD7jKwKxseuhowApEFnR4JCYpo9e7Z8bp1PrqMCQiidOnWSz7GzDhQfEUWCghiUmJTkOCeQJ9eJZ6+EqCSi19kHF8DDXkVghQQmJLOAHlId6iI2MUjr3XfflWVgkLaQ7FAPkeKChKX5S2b2J2kIGFklDcr0ySgKv/B0aKQYOjmrFowfP16kKD60AIHw+XU2Pq+O8TtIAEpA3M/GOYHjICFBXtyXX9D74q/zfCQ2JDBUwT59+giRQqBjx451TzzxhPvggw+EQFloD4kPFTH4/Pg87bz4CBhZFR/DtMtBOywSiKonFDLY4cMsNBKRPlclDvaUS0mK5zNq9+mnn7onn3xSDOaM1A0ePFhW2sTeBAFAGtyXF7FoPePrEkwbPNZ0ecXpNd2TJpg/Eh3qJ6srzJkzR6SsN99803344Yeimvbv31+kPurNBgZIXNjfFAuOqY+FoiFQxr88+f/0FC1Pu6uEEcCAjPrCyBmdi45PyK/TJ7u4EJN2dl4vNiUwyoYBm8+mI52wR5WCCFhGhdE4OjRx6RK0DtSJulEXRiEhrddee00+ZtquXTt38skny5pVSGQQFEFVRKQu6pUIUaZLvdOtHEZW6dYiSSiPqkZBtUSPU9FZ6MwQIx2W5xKI45gO/sYbb4hEAiGh6iGVsMomkpSWLyjVJAGSYmdB2Skbe/19h7gwxiNhsRFOO+00d8YZZ4gKqYTFfVov3Re7QBmYgZFVKWx0OhQqh3YMft0Jeh52lVUSUQkLosKBE5JCEkGyYvnfX/3qV7LOE+VTO5GqSqkqa6JYUCdwhUSDx4wm4ruFFPvAAw+IIb6Jd6W44oorxOkUKQscqGO61SnRuqdLOiOrdGmJJJaDzkQHUemkJDoLHZvn4tc0b948cQHgM1R0ZEbZjjrqKFH1gitrAoESnRJsEmEpVlZaLvaQDhvHBAgWQoawIGQGCxhZPPfcc91hhx0mo4uk4x6Vtji3UDgEjKwKh1ekUkMYdBBIQzsJ52EG7cDs8Zfiy8QjR44UAzqSFFuzZs1iZBrs9Bxr+XQfZlkLk7eSFJgqriplUVbiCEiNU6dOdQ8++KBIXBDzkCFDRC3EZqXtUJhnW9psBIys7E0oEgJIEvHSj3ZiyHHZsmXusccecx999JEYnemwGKFRi+i0dH46Lh1diaBIBSmBmygvIS9Cpe74jH3//ffu/vvvF7UQlRcpC58x7HIEzSOIg1ywP/kiYGSVLzR2IT8Egh0NglJ1E3WICcQ4dj777LPiTMmSv6eccorM04tX+bgvrw6f33OjEg8mkDlTeCBs/LN69+7tzjvvPPG8ByewIB3EzT6e+KNS11SW08gqlWiXomchQRAgHDobBIbah13q4Ycfls56+umnC1Exz05VJt1zL0RVGskKLHQaz4oVK9xDDz3kJk2aJHMMR4wY4fiwBAEpi3RImKYeCiQF/jGn0ALhsYv5IaAkQ2ejczIZmJE+pqQwqXjYsGGuQ4cOshyLSlDco1JZaSUqxUvrx6oNEBT7l19+WSSoiy66SDzjkUJtlFAR2/veyGrvGFmKOAQgHCUrjpnT99JLL8m8uaZ+Tt2VV14pU1BwR0DqUukL6YH0nBOC+cQ9IvKnKimBE575+F+hGr7yyiuCDR89ReJEJSStYhL5iodYASOrEMEtrVnTASEaVEEWu3vuueeEqJhDd/HFF8tcPtLQAUlHUHIjjmM6Lp1U40sbVlpvrSOrRJxzzjni+Y70CYmff/755tVeiIY3m1UhwEpFUn3JVSLhnE07OceQBHscLVElGH1i9G3+/PkSt3r1alHL+NXG3we1jD2qCBNzWVUAAy9zB5F+IAw28tVj6sr9avjleZRJJQbIZtGiRWJAnjBhgkgOzOujU8arNnkREvnlFZ8KjFPxjPj6gR2Y0U533323mzFjhrvxxhtdz549ZYRUcSed4qL7VJQ3Cs8wySrNWklJiheVF15femxDXMNbmgnAGG554Zlbxzw1rkEkEAz36i868WoMJ55jyItF5Vq3bu2aeCdNSIylfiGZoFuBEhP3cKySEgTJSp2PPvqojPgNHTpUJh+j7nB/IqG0d8T4+oEdPwwsoYyEtXTpUvfiiy+KOwML+/HDoW2dCH6ZmMYkqzRrdciFAEGw8ZJDFEhROBt+/vnnsigcUtSB9Q50DRs1dNiJWIaXUSZIB1uITqbFgxxyQ/pijXI2OgoTnSE5Osmhhx4qy5107txZ7Cks8Qvp6bMVIspGHPcy4kd56HgsiMc8PyVITW/73AjQpkhYYIdkxeTt66+/XtqM1OCrAfIKnmt8pu6NrNKo5XmRCbykBFYoYOldllFB1cJvh1/njh07yjA4EhIqXVAqUgmIl5x8dFMJi2dAfBAYeSOZQYAYyZGKWAlzwIABInFBWkhbSpoQGEsL40OF7xBGY3yoWNUhqE5K4e1PLgRoC9oBHJGQn3/+eTdmzBiZyI2tTydya9uRVtXwXJllYISRVRo1OqTAC82eaRtIMBADUhRk0KtXL9evXz/5kAEEBTER+KXmBc9LslF1hBefTe/hPiUu3A5YPpiF5SAw8j7++ONl0TkIkQ7DhvqH6scUGkjq7LPPlg5G2TSYJKBI5L2nrWhjyAq/tNtuu01WorjzzjtlnXdw1nak7bT98s4ts2KNrNKovXmJUddQ05hPx8JuSDsDBw50xx57rGNZX32BIQXIh0Ac97Lpy61xmj54LT6tdiA6DxIcZIQ9DPWQuXxMOkbKgtSYqMtzKRM2KiU/8qRM+vw0gjWtigJ24E27ckwbQ1So4Jdeeqmo4UHCNzz3NJ+R1R4sSuSIF1aJBLJA5Xv66afFgM0UDWwauta3zivTgnIfIb8Xem/Xg/loOVARMZ7zsQTWG4egjvEfU8AvCCmL60hSjC4iBWjZ9VlKXpq37XMioDjpnoESVMFnnnnGXXfddSI5K65gGSSunDll3lm5P/uQedUu2RpDDMGADQMSQKJ55JFHRLrChsHKk6xBrraj4D0cq9QUH6/ne7uu6eg4bKSHiLBBIcWx9vnChQvdJ598IqOPTERWtwclJZWmkBboZPkRpz4r0/eKMziAFS4kYIoazlr0LCnDjxKSF2mNrPa8MUZWe7BI6RGdmw4PUeEX9eqrrwpR4Qd1ww03iKFb59SFTQDkH79BWnzks2vXrkKezPmbOXOmkKeqf1ou9tqxNC6lYEboYUGcwYx3AGJiz48CEiurpuqPgJHVnsY1stqDRcqO9NeVPb+mTMFgw0GQpUSQYPQlplCpIgAtlz6PjsIvP9Idv/asmc6KCvgK4SaBhEg5MdQjVaWyrPKwCP4BY8WZ4nMMzvwwffnllzLKylLP/FhAYtoWEaxq0ou8x6kj6VlbhvkhwAuoI3F8RBPnQH5NdfIvxKD2KV7mVAXKpc/TDoUEiFc6hnYm5LJOEzY1bC3BjsRx8DxVZY7qcyB68IKoICU+54UKCL6fffaZGOFxXbGwBwGTrPZgkbIjiACJik+VP+G/QcdHPJn8i9rFi8sLrB0/eBxWASFOtTnpM5S0KA9BOxQkyoghSxVTbiQvlapIp+Xm2EJOBMAUkqJNCWClpMU1sGUUFh84VqxgZoHhuQdDk6z2YBHKEUTACxnc84vJF36ZAMwSvywZkhdR8aKm4mXVX3cA0GcSp0SJqseGt/sJJ5wgI1bYryBaOhZ2Nws5EaDNlfBzXtmDMfHavmDNO4AvHY66C/3ABnkUNigh5vfswuaXTumNrEJsDV427fDs9UXCRQFnT0YAGa7Wb+Xpi0uRlDRCLF4sa55F+YJBn6/xakNDJeQrxA3qNxAbFovKUU8IK1j+YF6ZeAwW8YRBHDgSFCv2bPyYMUUKVxXeD37MdK2wwuKneRf2vnRPn/MNTffSRqx8dGJeQl5aNo5Rt/ACZ14eToAYq3EV4CWOyktGma+59hpXoXwFcRLFzlIUKSBizVmo4tLetCd7fQ/Y67sQv0eVZsOXrX379mK7wlQQfH/i78nrPPjMQhU4Aolt1YUQGwkC4mXTwHQV5tTxEQU8lhn9w+bDC8aLzJ4t3QOdqkWLFu7iYReLMyMf+Lz88stj9rZ0L38qyhffjkieTLERySrPMZPsHzTSdWzfwb3vR14XfLfAVa6U0yaYSNl372apHz/CWLNGIskjk8bIKsSm4oVFjYKI2GPfoWNjSGXuHSqVvtS6D7E4ScuaukCyfPL9iy++kDmFLLzHsjPEW8hW85B8tF2ZFYDT787t2XMD4zEiHT9skNWSJUvcKj+x/Bk/6tq2bduY6hh/T17nPLOs/5GsU7uOG3LWkLySRDbOyCrEplM7Di8iLxEjaDhXsqwKw9R0euJJx2ibvtghFikpWVNm7CmMVh1zzDEygsVcRgzELFVjYc/KGWABXgsWLBApdNXKn3OpzF6mcrt3eZ+18tnLPu/4hdB+XPGjG+8/mJroe0E+PKtihYpiBzWysjcxYQQQ+dVOwSoKqH84/2FEZQoNgRdR3QMSzriEE9IhkKCoG/YVJCzcGXAY1S+3iLrjy0naRDtbCVcrqY/XerPXgBq4ZcvmXGQl13263VuzXPlyfkke1Dj/b9eunW5nmR16e0J7jAhZnvi2e5NDaQtmYA+xRdUOxQvLEsCM8HTr1k1WK1BJio6sW4hFSWrWQdW2Vq1asiIEq0Xggc1eCTqpD41YZkGC1uOytLWvR56bv1ZOJG1vMpB3wi/EV1D6/PIRmst+RsQg22txjaz2ClHxE2CLYGY96h62HfyVoh4gYEgL0sXYjoMoZIxtBrLSjXoGpYuo19vKX3IIGFmFiL2OBqICMkmVVQyYZxf0+A7x8aFlDflQN8iXwIABqiAL97FQINdVmgitEBHLWKUpKTaaYRhbxDApbHGNrAqLWCHSI13QoVnxE0c/1qVSn6pCZJN2SZGoICMkRkgL6Yq5jUy+nThxYsxdwwgrxU23xzyW4gen5nFGViHiTGfGt2ratGkifeBbVRo6MJITG+Skxyxtw2RcFu2Ln4BbGuoc4mtiWSeIQEa7LtDRCOzpUHQyRmzYIzGg3qhdhtG7wnY68uDrMnh4swZUkyZNJL/C5pNgW6YsGeVXqYqHghN1Rc1lxJNlmZk6AplZ+AUBj5l/y7K1P3TCEINqmCE+okSyzniyQlWDkJgGM2vWLPfOO+8IWbEIGh9OoFOyAB0G5MLamsiXZYF//PFH17RpU/lcVdSJSt9SxULrgyrIHEdICn8yiDkoeYFFpgXFJlZvT1KpIJJUPCNWpxQeZN4bFAcuLxSqGnP1Rr08Spwdr7rqKlm/iRU833vvvbg7CneKrQrDM6srIIGU5sC8NgiKta5UPaS+mUhUpbmdS6puGU1Wqv7Rmfhu3ldffyXrYUNgqDT9+/eXiaXBaTGFaSikNlZWYJoNxnWkj9IcwAlnUYgfL2wLhkAyEchosoKkUPMYsYOgmELC/C18hbjGvCyG5PGLyiXSJ9AK3IOTJNIVKxWoWpTArZFMwkgnX2ZevWq127Ez+1uGRcEtkpW3QoeOQEaTFSSF7QX1DHsL5ISn+T/+8Q+Zy4UkdPrppxeLrCBDSBCiggBLc+dFkgTPnX6aSFANDP0ttgdkBAIZTVaMYKkqyJw91hnnE1RMG3n55ZdFwoLIIBo6YmGDdlgISklK94XNKwrpIXdwVGkSzBSDKJTfypjeCGQ0WSH1aGfCNQE/qKFDh4payBA8y8uqiki6ogYkquLcX9Tnpvo+6onNCswYtICsgkSd6vLY80oXAhlNVqgs+ECxNC+uC0hRzN3jc1j4WrGSAB0PoimKRKT3aafl1SnNpEU9mVoEjrgwIGkVBbfS1cWsNslCIKPJCiLCJ2jq1KkiCdC56Gj4VWEsVimhqB1OpQokDqQ4VYuS1Xjplg/1Y/QTDHWytkqv6VZWK0/0EMhosqK5WJXx/fffd8uXLxcpis5Fh2NhucMPP1zsVcQVlbCwi0F6rKdNZy7NgYEENogqaA8szXW2uqUOgYz2YMeugnTFgnEPPPCAa926tYzY8ZmpU0891R111FEiJdDxUBMxtBcmQHCoQxidWSmSyb7q+V2YfKKSFl81jOs4h4IZ5FzaR0Cj0jaloZwZTVaQCSOAJ554onQspB8kA1byxMERnyFIioCKWNiAfQqyQqVEgoMcdYXQwuaVzumVlCArbH316tUTUtaBBXDgONOC2iyD9WZaYJhTAzX/MJ8RrE8qjzOarCAjNg1NmjTRw9i+KCQVu9kfML8QyY11niCroqqTwTxL+lgHCbQzQlYcMwcSFRr3D5UguYaUlalBsfIAuTJsHogyRR9Y3iuM/vc3+xl7TRm9BJn3c5fCNoKYateu7Vg+BWfTlStXlorRQCVc3SM1IVExzQa1ul27dkJWdNRYZ00h7vao0omAkVWI7YphHuM6tjCWnmFVBySN0hCUqKgP9WTS97Jly0SqQtVFmiJNJktVpaGd06kORlYhtgadFaM839PD8IyTKaE0SBuq+iFJYedDckQN7N69ew77lJJaiDBHJuuY9ie6oC92GPvIoFH4ghpZFR6zhO9QyYIVNJs0aeIWL14sTqh08CgHVe+oH7YpiOuzzz4TKYqv9xCnxnXqWRrIubjtFSOq4maUwfcbWYXY+NpJcZI87rjjZPWFr776Sgzt2uE1TYjFCC1ryo4KyGqofJkZQuZDp1o3yIzjTBwJDIKuUiiEpVvwOscav+d9yF5VVNPFrv+SVuPj95IOW2H8hVJwbmQVciPSUdmYxsM39nBAZcQMlwjt1Ozp9Hte1JALVczs1U5FNkiJqLcLFy6UVSvwKcNOp7YqUwOzJUslrDJlWHnDd7tcW/ayx8TLmKEnej3ec05c9pZFuvjN65WQlFhFSVfKQka7LqSiLXlJISvWYD/66KPdQw89JFN8+Hw8bhEQlKaJSsemPgTKzQgnK1Qw4tmjR4+YH5kScVTqlOx3QaVK8oW4wax6tepu+9bsCd7xzyvjr4MnHzrl3m3bfTo+Ke/vZStT9peVOzwbidyUn+jkOapC+Qo5XHLinxXVcyOrEFuOl44XkIChvWPHjuLdrZ0blYmAVKUEIBER+INRnTJ/+umn7rvvvnMXXXSR+JMRpxKiHnOeaaRFu1NvMOC4SZMm7vzzz5eBlqysvEaEy0haJFWk7vHjP/S4LnBDh14Qm0XB95whKvItVzZv3zVID5mqWvVqEXiLCldEI6vC4VXo1LysdFT2LPDXr18/N2rUKPkwBS8vLx4GaQhLfkF92igE6sSKqh9//LHj4xrUC2996kPINHLKq81oc8WCQZZzzztX2jivtOAFdvwI4K/29cyv3b7eYfnSX/9apCSuK6akU5zj89J89Ecy/nqUz81mFWLr8SupLxW/lnTmk046yR144IHyIQrmIOrIYPBlDLFIScmaMuOKMXr0aJlGdPnll0vdtHMm5SERzwQs+AFiI+iPkRJN/B5yYSPd3Llz5YegZ8+e8kMWfDf0fdK4+D3PIo4fvtIWjKxCbFGdcqIvGKOCENXFF18s6z699NJL8jGJoLE9xOIUKetgpyIDzpk29M0337iRL40UvyrUWzqndhxNp/UmPhODEgb1VyJXjPLagxHOw4wYM0jBoAzvUBA/va8gPME9eE9BaaN0zcgqxNbiheGF5UXFZoVBHe9uPkLBl3Peeust9/bbb0vn51eVlwypRY8555dWO32IRc0za30+ZKplonxIhP/6179c/Qb1ZdI3gwdKzGSkHUr3eWaeAZHUX8lGVXzFJH4Pvmy4gfDtSqYs6eoVeUEVf3/wXIkxr/uiHGc2qxS3Hi8Vv5oDBw4UB9EXXnhBCI0PU/CSsZEGgtDzFBcxx+OUbInEnoKK8vjjj4saOGzYMFn2RjsK5MaxhcIjAG64tGADZJ4lo8XYAg3PPViaZLUHi5Qd8WuLOnjppZeK8ZTRwYkTJ8rLqhKM/iJzXlJBOwp7VD+m07z44otipzrttNPEFQPiDaYrqbJG/blgyDJCb7zxhkzP0rXPFNuo1y8Z5TeySgaKhcwDCQT7Fd8SvP7668U4fffdd8ta8KgBqH6oW6RTSauQj0hKciVOysLigSxQyIc0WANs0KBBIiFCqpQTSdBC0RAAP9ocbJljeeyxx8pHdml7C3sQMDT2YJHSI15QbFgdOnRwl112mdgnIAN+WdetWxfr/EoYKS1c4GGoJMz7++9//+s+//xzd84558iIJiqK2mFIrqQVuNUOE0QAoudbANOmTXMtW7Z0jAJi4+QdsbAHASOrPVik7EhFezo465XzCbCrr75alj9++umnHXasVatWiY0o/tc1WS8w+eSXF/FIU3z2npEpiGrOnDnujDPOcGeffbYQa5CckArSwb6WsgZMwoMUf36McAP58MMP3YoVK9xZZ50l07L4IStJE0ASqpj0LPzihUbfSUe1kBnSBLyY3377rXvqqadk/iBLrZx55pliaOXFVYKDGDjOSz3UDqBpOec4ryZWiU2lIyUcLQv2qddee82NHDlSlmUe6r+niHrCLz5bPIkWssoZm1wJSPfgPmf2HHfFlVeIRHXdddfJ6rIABMa0j4VsBIys0uhNwMeGX9d3333XjRs3ToiGj1ZgI+JrO7g98AIroeiLDCG9sStTAAA5uklEQVQFCUqrpGSl58G9kpWSDudsLKI3ZcoUN3bsWDH4MoQ+ePBg16JFi5gnNc/V+4J52nHBCGi7gbO2GcsG3XnnnbJwIUTFEjv6A6JpCs41c64aWaVRWythMPI2Y8YM9+STT4oaxhzCIUOGyOgbhnlG4FS64YVWUlLCokraIfKqHum4rkZxXBJQRTDuPvvss2I7wSaF2jdgwACZhE16ns2zCEZWeSFbcBzY0bZKRqjZzz//vHvmmWfc8OHDHSOsrMwB1qTVdAXnmjlXjazSqK15SVXNY4+UM378eHEexQCLuwNezUg7GOZZjoUXmsDLzaaEpSSmLz7kwnEwPZLcQr+0C3Yp/HtYk4qPWxxxxBHu5JNPdk2aNBFiJC8lJ/IInqcRfJEoiuLHjwOY33PPPeJPdd9998mPApWgjUgH5tqekahcyIU0sgoZ4MJkj4TDy6kbv8LEIfFAKp988olMc0HCwWucZVkgFEaQ+HSY2pOCL7iSGAZz8mJ07/vvv3ezZ88WdwQmI69fv16M5jgiHnrooZIfkhWdBUO6Eqh2NPvFL0yr7klLW2g7LF261P3hD3+QHxgGV7p06SIkBbakI7AHfwvZCBhZpdGbADlhTCdAOEoSkAZEgw8WM/KZjoFdC49niAtbFp8U43t9kBdqIsTCy869qHuQEhuGcwiLZ7GHnE455RTXqVMnMeySH2XgHu0oHGu5gmWjTDxH43gWS5ewZ2MNJlkNzu8yOQTJB8yQmG+55RZR9a+99lr5biVtSOA67ccezMHRQjYCRlYReBN42XWDHHRDOmL6Cyoirg7YQOgIkAtkx4vOfZAOHQB7CBIZzqioknx1R/2l+EUXgvH37S1AohAdKioDAnwbUT7m6heXq1Wzlv/8WC2/nlINV2kf793uM9POumu3H8mExALPKI2dkfrSRtSTDWmKONqFNnr44YdlTig+a0yz4kemNOKwt/eosNdNxiwsYiWUXl/84EsN4TBKx68wkhLqHJ2BzqGEQKdRsoKYIBakJ1RG4lV60vSJVE/LQOfDJwyCrOzzrOkJqlqVqtnkVa2qJ6zqQo41/Bep6ZDVa9aQNdrxLaMs+uxEnhmlNIolpK515HjDhg3uiSeeEOdaBi8wqPPjoWQepTqWRFmNrEoC9SQ9E2kI9U8XvcM4DpFAUGpXoiOw0Vm4xkZn0g6iHaswRYIMCRAlpINkB3H5xXflXwVPgrv9aphYXlBvKnsJq6wvK4vJQZasOvFrv6gcx6U1gKvan8ALyRe/NWYonHrqqTITAOy0TUorDsmsl5FVMtFMcV50BgLkxEvPrzgkpESlxaHjYP9Q4iKeOO5j45j7Ew3kj2SGgR+bFx+MkDJAVbu9EXnXL58a8/miLrLt9GRZrkJ5WaUBiRDpjueW5kD9kHiRPB977DEZ1WU0l3mVuqyO/miUZhySVbfE39BkPdHySToCdArt+EpIkId2BK5pvD5cz4P36rVE9tyHHQyy0nWXfJRnQf5nkx8EyHOQLMqVL+fq1K4jfltdu3YtFDkmUp50TANJL/SjuCypw7w/VD8WXqxfv77UH1zAR9suHeuQTmUyySqdWqOQZRES8FKOkgK3B485146gpIQ6qB1E95qG9IkE7kO6ghD52nSzZs3cSj/SuHOnX8LXX+N6FsIVxOUZrLyX6sp7qapb927ija8jjok8K4ppwBiJig9pPPLIIzIRnDl/bEhUtBFpwBCsLCSGgJFVYjiVaKr8yCRetaOQwZdfj7mfY/Z0EA10mqIE8lGiZISRUS0cSnft2JndCb37glcwxU7Fc1EZ27Rp46666iqRwiArgqiOvgzsyZNNQ/BY40pqTx20rJQh/piyqk2QPRIV65MhUWGruuSSS9wJJ5wQG3klDzW8c2whMQSMrBLDKS1TKQFp4TjXAJngJY2BO+gjpdeLu1cJDiJCusLY/s3MWS7L26yEfMplEyEdmZFCvkiNQZ1Oqp1d0vnrSprB8qcTWYFVsGzB8lIHfgAgKY5x9sQz/fXXX5f6XnDBBQ61l9kGYbRDcdsxSvcX7ac1SjXMkLJqZ9JfeT4+OmnSJCEsJYVkQUFnZYMQeR6jWn379pWRyd3elwq1z/du6eAV/XHFShXdu++9K3YbXCsoD2oSnZz7KbuWkXO2dAqUR1U2yqpl1D2uI2DBAoUPPvigGNPBZMSIETI9qqZ33YDUleTSqW5RKotJVlFqrTzKqiQVvMTiffg/8QuPfxPzCFVNSQYR6DO1syIxdOvazb01dpzb4J+9c6f3foekfAfF6RGp68OPxrs/33yz6+8nRrP+PNIY6mCw89PhCemoIgXrzDHkSgBXfhimTp3q/vOf/0jZjz/+ePmgqY74UR/SEdKxblKwCPwxsopAIyVaRDoR/k6s6DlmzBiZmsOibk2aNEm6TxOdlY7HMyEdjOwdPSl+6xfpQwqRkUK/qKAs1ueXt+nsRw1Hjx0jU0xYwhnViAnTrDWOnxj3qKSVaH1TmY56qmRE3SEf7FEsSsjUpy+//FJmBbBKBXMsISoCGJGee5XgUlnu0vSscn/2oTRVKJPqEpSSOEYy0ekcGLwx9DIdhjWS6DzJIgOVqMCaY9Qg7FGMCDJEv9t35OZemrraz3tre0g7f62Gq+sJ65D2h7jmzZvL2k3YdGZ/M1u8ulkCh7IpIQTzT4f2pFwQDXtIChUW2xQ/CBjRF3r3BAzoLPPStm1bWayQtNSJ9ME9dbNQNARsbmDRcEuPu6QTeRuKLw0e45s3b5EO9B+/3MiSH5aIsRuppWu3ru6uf93lqlavJuVWVYQORaADqdQgEUX8M3/efPd/f/yjW7R4kbvyyisd6lAVP/2GAtLZea5ODUISefXVV0UioRwY4PmW4sEHH5xj1CzYuVUyIY5jtngC5hr5Be8LVodrusXXWe8Npg+SzcYNGwVXpFW++cjEcpakZkVX1FrUXupIPvF5B/O046IhYGpg0XBLi7vgmizfYcsglXgTyk9eihr95puintAh6chbtm5x38z6Rj5X369/P5mvR+HpUGxIY0pexa1U3f3qun4D+ot018OreFU8UVKO8uXKS+elPHRobFyHH364a9iwoZDVp59+Kuoh62rR6XFzYJI1zpOomKiUdH7yUhJgr+QSjOeYoHuOSacheEwc6TSOYz2HCDlmPt/PP/8sE8aRBKdPn+42b9ks5eRL1HzcoXbt2lIvfYbtw0HAJKtwcE1JrrgJECCszd5N4ZVRo9zfb/u727xps0gzXMObnDl5kMPv//B7UcPonKqa0OmVAEhfnIDUxGRq7GaohZAMQclAjyEBJBZ9LrYf5he+99577oMPPpD0rM+FSsUoI3Yt8qLMECv3kYfeT/66yQP9H65rCD6feDZNzzFlYSNwDlFRB0iK8kyYMEHsf9QPgjrxxBNlzygf5dK6UD7In03rrmWwffERMLIqPoYllwPz8HzH8D3PzfTz82666SY3xy8ZU9af05Hlmi9dZdZK8p3w936xt9MHnS7SinYspJxgZy5OZVQ1Iz+OCZAL5aA8SjLE6zO5xjHkoGQ3ccJE98mU7IUGsbsxWRuJq0ePHiJxQRI6gZt6QDBaH55LfkFpUcvF8zU9ZSBwjWcwggrRYotigIINVwRIlxFVng1JYfsDM/JnT+B5lIFN66V7SWB/koKAkVVSYCyhTDxZ0cnXe1XlXr88Ll923uDtKHRKsWP9QhisIQVZdfXTXW688UZZaI9OS6CDSXrf4YobyEulDCUrnsMxzyBovHZwfSb3ErifOrGwIGQBabBSKlLOmjVrhCAwyCN5oX6x4XDJsjMQGP5NHEMmSh48CyLESZalnNlDTDwDksL1AJLiGah93A8poYYy6RoJjw92oJJCUIqdlp09z9LnaV2D1+24+AiYzar4GJZcDp5f6ITTp38hPlV0NDopxnb/e+/32RJHlj9HHUT6YokSOh8dDvsRHTmZUgD50mnpsGxKXronTq8Tp0SmZaBMbBAPhISLA/Xi0+oQCq4CrPLAwoOQC/kh/eCpr4SlZEWePIsAASJB6YZxnHwZ2SM9hn38wVA5mzZtKvY0nq/1IA8lWq0L+6AEp1gSnxehkYeFoiNgklXRsSvxO7N2+ekdy5a5f9x+u3v7nbfdTj83jw5Fp6HDIFFxLlKG3+NJXt1LIbf79JAAUghqGNeVLFJdKSWT/J7PdTbKqRt1o15ISKwnD5GxXDNLsUBA7LmmxEhayA/1UUmtcePGIjlh5GfVCAiS9GDBBtmw5VeuVONkz/MmBQMhughs2rzJzfhiups4aaLvaOW8lLBJVjegc9LRdvm97+liw9rp91u8ZFHBd0oWgUN6QKIo6Q65NzLgOptKXNQN8iKOSdQQTfv27SVOSUz3pCEt59QTFU4lJT1X+xNvAektpC8CRlbp2zZ7LdnqVavdqFdGiYrDFBeWD2Yvnc5rP6g8GNe1Y/puLtIJw+/ffPONSBZRGrWCeAjUh8A5ZAORKdHonmsQm0pXxOs14pXAuK55cY+mkUj7k1YImBqYVs1RuMKs9kP+M7+e6TZ5+wtz8ejEqEqoQuP9xxyw77CELlNhyvlOiT8WH20gYKTGl4kOWpJqYOFqnJ2aMhOUWCAfPaf+4MA1Jav4dJo2uI/PUzK0P2mFgElWadUchStMlSreO93bnuhobKxzjs8Vo4P4LeHF3q1bd9e2XVtRB3VddJVMMC5jw4lK0HpCPkpAlD14rERFHFJT8JoeKzFxb/CYcwvpi4CRVfq2zV5LhsF8t1+dE3sVUoTvnzLqt21b9jfnfJf2w+0VXaVf1CRPaTJCGOz0qENIVlEJlD1IOnqs5Ve1jnO9Fk9IGq97vdf26Y1AdN7S9MaxREpHZ+MjDAQ+LioBGzFmGD4wqhss5o/5V94f59d5szNI379SXy89alCy0b3Gx+/3dj0+vZ2nJwJGVunZLoUvFSSVX/jlmnZa3eeX3OINgXREIHsoJB1LZmUyBAwBQyCAgJFVAAw7NAQMgfRFwMgqfdvGSmYIGAIBBIysAmDYoSFgCKQvAkZW6ds2VjJDwBAIIGBkFQDDDg0BQyB9ETCySt+2sZIZAoZAAAEjqwAYdmgIGALpi4CRVfq2jZXMEDAEAggYWQXAsENDwBBIXwSMrNK3baxkhoAhEEDAyCoAhh0aAoZA+iJgZJW+bWMlMwQMgQACRlYBMOzQEDAE0hcBI6v0bRsrmSFgCAQQMLIKgGGHhoAhkL4IGFmlb9tYyQwBQyCAgJFVAAw7NAQMgfRFwMgqfdvGSmYIGAIBBIysAmDYoSFgCKQvAkZW6ds2VjJDwBAIIGBkFQDDDg0BQyB9ETCySt+2sZIZAoZAAAEjqwAYdmgIGALpi4CRVfq2jZXMEDAEAggYWQXAsENDwBBIXwSMrNK3baxkhoAhEEDAyCoAhh0aAoZA+iJQPn2LFv2SZWVl5VmJMmXKOL3GsYbdu3c7Pde9XiO9xgWP9brtDYHSjoCRVYpaWImGxylRxT9a0+g+r7Tcq6RWtqwJxvEY2nnpRcDIKuS2hVxUEoKE2CAbQpCUgvFBEtJ72WsgbTBfjbe9IVCaETCyCrF1IZUgIUEwEFWQjILXNV7JiKIRp4SlReW6ptU42xsCpR0BI6sQWzgoDekxezZV5cqVK5eD0CiOptFjJTT2el+IxbasDYG0RMDIKsRmgVx27drlduzY4bZv3x6TkILSUuXKlR2EpYH027Ztczt37pQo0kJQ++67r6tQoYLEKfEpiem9tjcESjMCRlYhty5EtWTJEjd//nw3d+5ct2bNGgdB1a9f37Vo0cK1bdvW1ahRI1aKdevWuVmzZrkvvvjCbd261TVp0sS1bNlS0pYvXz6XFBa70Q4MgVKOgA0nhdjASEdITbVq1ZLt22+/dU899ZR75513XLVq1Vy9evXkOpKThkqVKrkDDjjALViwwE2aNMnVrl1byAypCqnL1EBFyvaZhoBJViG2OJIQklXVqlVds2bNXN26dUUyGjBggOvVq5erUqVKTLVTwuKehg0bugYNGghJHXnkkZIGdRC1Tw3rpgKG2HCWdVoiYJJViM0CASFZsaHSIS1BUH369JE98ZAONij2bEhQ3Pfjjz+6Hj16uH322UfiSKO2rqABPsTiW9aGQFohYGQVcnOoBLRw4UK3dOlS16hRI3fggQcK8SBFKaFRDNJiXMfGhQrZpk0bieOa2qvUuG6EBSoWMgkBI6sQW1tVNohlypQpbsuWLa5z585iYFcpicejKmrALjV79mwhKuxa8SGYZ/w1OzcESjMCRlYhty6SE24Ln376qahzHTt2dBjRIR2VqlD9VGJCXWTUkHSojJAXQSU0jrmP82Ac8RYMgdKMgJFViK0LAe3aucst/WGpW7xosYwANm3a1FWsWDGmBirpYL8i4NqwevVqURUhtXhC4py0KmGFWHzL2hBIKwSMrEJsDiSgbdu3uU+mfOJFIyeuCs2bNxf7U16PRR3cuHGjqIlIVRYMAUNgDwLmurAHi6QfIQFt3rzZ4V9FQKrCATReWuIaUhgq4OLFi4XUglJVXum5x4IhkEkImGQVYmtDQKh1y5YtE7UNb3XUt/zIBwP8119/7Vq3bi2qIkVTW1aIxbSsDYFIIGBkFWIzQUobNmwQGxRG9CZ+6kx+5EM802xI3759eyEr7s+P2EIstmVtCKQlAqYGhtgsEBAbI3pKPNix1DhOHNeJQ6qaPHmyEBpTbEjDNU0bYjEta0MgEgiYZBVyM+ErVadOHXH2xHaFs2eQxDCqQ1RMXF67dq14rRekKoZcXMveEEhbBIysQmwaJCc81k8++WQhqLFjx7o5c+aIqqfS1KZNm9zMmTPds88+6/od109WVzDVL8RGsawji4CpgSE3Hbaqnj17yhIxeLHff//9Mjdw//33F38plo6ZN2+eO+6441yXrl1kLiCSlxFWyA1j2UcOASOrEJsM0mFOX82aNd3ll1/uunXrJp7sEydOFDeF6tWrO/yuBg0a5Nq1ayee7RSH+ywYAoZATgSMrHLikfQztT/hc9W1a1eZRoPjJyTGNVZV0GMejkSlW9ILYxkaAhFGwMgqxMaDdLBNEViWWPcsxqdGdiUmVf04D17TeLnZ/hgCGYyAkVXIjZ+f6wGkFAzB8/yOg+nt2BDINARsNDDTWtzqawhEFAEjq4g2nBXbEMg0BIysMq3Frb6GQEQRMLKKaMNZsQ2BTEPAyCrTWtzqawhEFAEjq4g2nBXbEMg0BIysMq3Frb6GQEQRMLKKaMNZsQ2BTEPAyCrTWtzqawhEFAEjq4g2nBXbEMg0BIysMq3Frb6GQEQRMLKKaMNZsQ2BTEPAyCrTWtzqawhEFAEjq4g2nBXbEMg0BIysMq3Frb6GQEQRMLKKaMNZsQ2BTEPAyCrTWtzqawhEFAEjq4g2nBXbEMg0BIysMq3Frb6GQEQRMLKKaMNZsQ2BTEPAyCrTWtzqawhEFAEjq4g2nBXbEMg0BIysMq3Frb6GQEQRMLKKaMNZsQ2BTEPAyCrTWtzqawhEFAEjq4g2nBXbEMg0BIysMq3Frb6GQEQRMLKKaMNZsQ2BTEPAyCrTWtzqawhEFAEjq4g2nBXbEMg0BIysMq3Frb6GQEQRMLKKaMNZsQ2BTEPAyCrTWtzqawhEFAEjq4g2nBXbEMg0BIysMq3Frb6GQEQRMLKKaMNZsQ2BTEPAyCrTWtzqawhEFAEjq4g2nBXbEMg0BIysMq3Frb6GQEQRMLKKaMNZsQ2BTEPAyCrTWtzqawhEFAEjq4g2nBXbEMg0BIysMq3Frb6GQEQRMLKKaMNZsQ2BTEPAyCrTWtzqawhEFAEjq4g2nBXbEMg0BIysMq3Frb6GQEQRMLKKaMMlUuysrCy3e/dut2vXrkSSWxpDIK0RMLJK6+YpWuEgKIiKUKZMGVeuXDkhLeItGAJRRcDIKqotV0C5y5YtK2QFYbGZZFUAWHYpMggYWUWmqRIvKJJUtWrVXIMGDdw+++zjIC8IS6WtxHOylIZA+iBQxr/A2fpC+pTJSlJMBLZv3+62bt3q1q9f72rVqiVqYMWKFUUlRC20YAhEEQEjqyi22l7KrFIUEha/RRAUcZwbWe0FPLuctggYWaVt0xSvYEpS8fvi5Wp3GwIlh4CRVclhb082BAyBQiBgBvZCgGVJDQFDoOQQMLIqOeztyYaAIVAIBIysCgGWJTUEDIGSQ8DIquSwtycbAoZAIRAoX4i0ljTNEGCkjyk06ppQvnzO5uT6zp07XYUKFWIOocQRcGOwYAhECQGTrKLUWnmUFf8pyAqigohwCN2xY4cccw5RkQbSIuDNzqYhOI9Q42xvCKQjAua6kI6tkmCZVErSPaTFMQSE5KRSF/F6zPUgWZmzaIJgW7ISR2DPT2yJF8UKUFQEIBwNSlwqcRHPscZzbtIUKFiIGgI5jRxRK32GlxeJCfUOKYr9xo0bhZi2bdvmqlev7vbdd1+ZIwhZrV69WtTFAw44wDFPUCUt8rBgCEQBASOrKLRSAWWEqCCjOXPmuMmTJ7u3337brV271g0fPtyddtppbsWKFe6VV15xzz//vGvRooW79dZbXePGjcXGpeohUpeRVgEg26W0QMBsVmnRDMUrBFISUtWaNWvclClT3GOPPeZq1qzp7rjjDvfuO++6KlWryHVWYOjTp49cw24FQRlRFQ97uzt1CBhZpQ7rpD9JiUbtUUhYmzdvdiNGjHDz5893gwYNcq1atXI9evSQda0gNUYHdbkYvc+kqqQ3jWUYAgJmYA8B1JLIEqJiY7G9gw8+WNwXFi1a5Fq3bi2SFPHYsJSotIwQlpKWxtneEEhHBIys0rFVClkmJCbUOqQmpKROHTvJcaVKlVzVqlVjuanqpxGk1U3jbG8IpCsCRlbp2jIJlAuiQSrSvTp+bt+xXSSslStXug0bNkgalZ7iJSnutWAIRAEBI6sotFICZVSpafny5W7h9wtdlSpV3JIlS2RkkBHDIEkpcZFtMD6Bx1gSQ6DEEDCyKjHoi/9giAYVUO1VW7ZscVOnTnWHHnao69mzp7gt/PTTT454SAwpi2DSVPGxtxxSj4CRVeoxT+oTcQDFlwoiWrhwoUP1a9u2revYsaPjGnHfffedmzZtmjiIQlRBsoo/T2rhLDNDIIkImFNoEsFMdVZIVnPnznXDhg1zhx56qGvYsKG76KKLZPSvadOmMio4cuRIt2rVKnf88cdLfKrLaM8zBJKFgJFVspAsoXwY7TvppJOEiHD4rFevnpQEp9ALLrjALVu2zHXp0sW1adPGloUpoTayxyYHAXMKTQ6OJZILo3/YrPg+IH5UlStXlnKg2nENWxXXMbYjhbGMDMZ2C4ZAFBEwsopiq1mZDYEMRMAM7BnY6FZlQyCKCBhZRbHVrMyGQAYiYGSVgY1uVTYEooiAkVUUW83KbAhkIAJGVhnY6FZlQyCKCBhZRbHVrMyGQAYiYGSVgY1uVTYEooiAkVUUW83KbAhkIAJGVhnY6FZlQyCKCBhZRbHVrMyGQAYiYGSVgY1uVTYEooiAkVUUW83KbAhkIAJGVhnY6FZlQyCKCBhZRbHVrMyGQAYiYGSVgY1uVTYEooiAkVUUW83KbAhkIAJGVhnY6FZlQyCKCBhZRbHVrMyGQAYiYGSVgY1emCpv9Z/zSiToevCJpLU0hkBREEgZWemXf4u7L0ol0+2e/zzwsJs+46sCiwVOP/ywzL33/oeO9Fdcdb27/Z//LvCeZF8cPeYt17T5Ie7rmbMKzHrFTytd3QObunv/82CB6YIX//fE0+6MM89zP674KRhd5OMNGza6NWvWFmsjj/zC+PEfu97HDXSz53ybKwkfme12ZG834srrcl3bW8Sbo8e51occ5j6fNj3PpP+4827Xok0nt/LnVXlezy+S/LoecYyb9sWM/JJI/GHderqrr7upwDTBi7f87XbXoElr+QBJMJ7j3/3xFtfxsCPctu3b4y8l5Txln+I6oOHBbvv2HcUqdMWKFdxPSxcUK4+Svvmjjye6P978V/fb31znOnfq4P55173+M+8/uA3+CzVr/bZ+/Qa3bt16t/zHFW7Tpk1S3PLly7mmTQ5yGzdudFu2bnX7/PIVmy+mfylxedWpXbs27pJfX+W+mT0nr8u54m679c/uVyefmCP+yCO6y/mzz73kbv/7LTmuFffkyaeedavWrHH71a0Ty+q8ocPcuLffi53nddDnmJ7upeefynXptMFnu6mf593hcyXOJ6LL4Z3du+PeyPPqk8887+Z/t8A1atgg1/XXXn/Tzf12vjv/3LNyXdtbxMRJnwjBtm3TKs+k73/woXydKIhTngnjIp98+jn/Xi11TZo0jruS8/Qn/1Hc9evW5Yws4Gzbtu2x9zI+2UcfT3D77ruPq1SxYvylpJynjKwoba+jj3Cn/urkHAXfsWOn27Fju6/kvjni409efe0N98mnU2PRdMI//+XvsfOCDh5/9L/S4AWlSfTahImTvaTzkDv7rMHulJMGJnqbpIOsb/ztH13zg5u5a68eIXFPPv2s2+kxgLjqHbC/a9WypatZo7p8WovPZvU+5mjXonlzB1HHh2uu+437auY38dFy/uyTj/g8O7o6dWrluL5q1Rr3/ocfue5dD3eNGzeMXTtg//1ix3pQq1ZNd8agU93Lr7zubv3rn5L2Ga+vvp7pvvx6lrvlT7/PkefA4wfIh1n1+cH9vHnz3Zhx77hWrVoGo3McN2xY3112ycU54hI9+e/Dj+WbdPXqNf7Zb7uLhp7vqlatkivdv+95QOL+ePPf/A/R33Jdf3vMK65rl8NzxRMBWR1xRLc83/+1a9eJZHTeOYUjwY0bN7lXXnvTDT7jNFendm15Lj98M77MLc3v2rXb/ew/gjtp8ic5ylexYiXX5fBDc8QVdEIeSJ3nnj2koGTFupZSsuJDm0PPPydHgf966x3uvgcedF99MUU6a46LgZM5c+flICu+lRckr0DS2OHmzZsdjbF7d1YsrjgHTz/7grvuxt95ct3penTvVqisUOsgqm/nfefefPXFHL8+x/Xt7e67584c+fFLjWpx1z//7tq1bZPjmp7cecet8tl4fu3OPn+YGzzoV26If0EJHTp0cANPGKBJY3vE+A+8SvPow/e7hg3qx+KDBzf7H4FX/ctO2LRps8Nu1bnLUXL+2qjn3Wuvj3YLFy2Wc/7wfULCG6PHugXfL5Rj/XP1lZe5g5s11VPZ86u/r//O4QXnnZ0j/swhg3Kc6wnP7+NVsCYHNXa/v+l6jc61r3fAAW7EZZfkiEdFS+Rbia/6OuUXXnjpZf8dxl3u0uEX5kry0CP/czO/me3OOfMM17lzxxzXH370cVFzD/Y/TsFAfb7/fpHj/fxmzlzXq9fRMfWyQoXy8mNG+vFeUuH95cftuwXfB7OIHdevf2BM0tbIkaNeFennskuHaZSbN3+BG3jK4Nh58GDCpCluQtw1fjjnzJwWTFbg8aTJU0Q1pMzHn5j9DuZ1w4MP3OMOatwor0t7jUspWcWXZsaXX7t7/vOASBGXXXFN/GV3mpfCzjvnzFzxRHTv1tUtWTA7z2tEok61bn+463BIW1etWtV80+3tAiTz7PMvuYf8L+/Xs2a71q1aOIizMIE8sAs85VUJJKqjjzoix+3z5n/n6MDBgAhPmO5VvScDHyblJerf71i5pr/WShbN/Cfj+/bpLdfy+gMmj/7vSXeU/yXPj6i4r1nTJq6bl7yCAbsVBMqHVMe+9Y78SteulS210aEIXP/hh+xy0yF53llDTs9BVsuW/+hQKy8cep7/inQNuW/Uq6+7I4/okeePlZD8TX+UzgzJ8zHXwoSXR73mbvA/ElM/+ShX/n37n+QOO7STu+O2v+abJfW47/6H3Ekn9Heo4pDf6LFvuX7H9XVjvbSFnYbQwBP/sIsuiOXDDxs/TH+75f9i0o1enDv3W9er7wl66h548BHZiGjgyWfWl5/JtVc8LgTMBmx5hTdeecH1PPrI2CWk97vu+Y8b0K+vvKtcQJWsW7eue+m5J2Lp9GDoxZe5jh0OiUn6Gl+pUiU9dNjN5nhSJXz9iyR/0bDLnPMf0+3QPvvet95+10G0rVu2iN0XPPjJ2zWRpjdvzv5hC15L9LjEyAo17oKLLhXx97qrr3Bly+6x9dMxRvqX7NRTTkq0HrnSPf/iSPnlush3iuIEjIVXXH2DEN49d/3DVa9ezV047PJCZfnb398sRPU7LxXcdMM1IpmVK1c2Vucpn33u2PIKTz/3omPTcPSR3WNkpXGJ7h97/CkviW30HS2b7PK7D4knKPVAhl2OOMYd26eXq39gPbkNae+j98fJMQb2Vu0OdTded5W75qpsbCCgiy+5Itcj7rr7PrePt2v85vqr5drUqdMkHbiATzAwwnjlNTe4518cJeU56sgewct5HvMF6m2eYJTUsOtV9h0Pkg8GVCUGOQb0Py4Ynev4iSefETXpT//3O7k2yqvEl1x+tbQjpACxD/REhu3xEP/DePKJJ7hPpnzqrv/N771K39xLYxflylMjkHx6dO+ip+6B/z7ilvxC9pT7zTFvu5MG9nfHHds3lkYPZs76xj386BOeL8polOyfeOoZt9z/IIx68Vk5ZwDjvKGXurPOHOT+dUdus0m58uUEG8g3v7BgwQL35VczY/lxAPEQqlatKrYxTAXnnDXE3f2v2yU+/s/rb47x/f3XsXc+/noi5yVCViNfflUkjTp1a4uITuM+eP89DhsJx3f++17Xu9dR+UpViVSMjlm7di13yiknJpI83zTlypZz/7z9b15CGCT2itfeyF9dyC+T7Tt2uNv+drNTsfwvt97u+CVSY+653v51793/zHE7ZDviqhvcxPFvu7ZtWseuxb+csQt7OUBC+O9Dj0oqOm9hwt33PiAjk/fddUdhbsuVdtHiJULaf/3zH6Wt+SFALYVIUBeDgZHQK6+9wX04foKQDS/7Ud7gjw2toICqjXT3/DOPS8f4YsYMby86zPHsq6+90T35v4ddDW8T/GL6DG8e2O2OCJBFfL6oaf++53538YUXiHSIpPjPu+7xpH2MO+H4fiJZjXzxGSn/Qq/+/nrEta5C+fKeYH/jalSv7l549gmRNuLz1fPDD+sk5Kbnb7w5NkZWt/z17yJ53nPXP+U91jS6R6qLJyvsUv/81z1umC9vyxYHi1r2Dz+CDCHF/xBoPonsH3rgXkkGXu07dxchYNqnH8eIEswJ112T+8dJLvg/SMiEor6/3JtysqLT3Hr7nV50PUIIarUfETrznKGuZ98B7tf+VwgbFqL5448+WOSKMeKGCH7F5ZfksA1R4cIGRNvhF+8R7xX0wuTzt1v+GDPw84uJ2I/RVNUgGjAoWZL3Tz/9LI84qHHjXNcK82xN+6yXzn5amZ3nug3r3aWXXyW/hEEVQtMG96ijuCT0P66P6927V+zSbq8OIZ0QGKUkQD4at9WPWsaHYZeOkBHhl195TfJkxJMOcP+9d8YMzNgD//fEU+4v/j3Y5SWrO277iwzKjLjyWjf8squ8tDHW3Xf3v4Rw4vPn/KSBx7vTh5wrhm4M+F9//Y2MvGK3Qhq45LIrhUSmTvtCBi0OOyx/IzLSEVLjlE8/c228SYHy0laPeXsf6s+H74115T05Ee6/799etTvenXXexdLWY14fKWqjXCzknw/9AMhHEybLjyQ/uHkFVb2DgtWV19woLg5z5s51R/XqJ/bDzV4qvvmPv3V169QRY/0nU7JVTM1zh1cbGeXEPSYYGBlmwCIYJn/yqVu6bLlEMdDEu8M79fQzL7gzBw9yjRs1dAgJn3421T3g8VBsuIF2JkSKrPhVHzf6Ffk1ouCMrtx43dXuMv8y/uFPfxXD6+W/HpbnqIvUNoE/j/4vWzy+8IJzE0gdfpIqVbJHkLAnXHH19b7uBziki2CgkzZqukeC2rlrp1zGx0ZDGz+8/eG7Y/TUIfHcfsddsXMkUuIIyxZ/GyM5OtmdXk1BhcNmhHH7uwULRZ1FlYt/KTXD7PJe58p4Ff3Of+RUIbDfNQyUl3tu+8e/ZNP74/cMSlSvVt2P+DX1pHKCpO3Qvp07+8zB4q6B3Q6DNR0CW+OD/hddh/RffO5JkQz/dMutbla/E0VyQnqID8d4Y/Vfbv6DvEvbt2+TwYGuXQ4VG939fhCDgQhUtulesjrUj5YWJGW2btVKRk1bt24lHfH2f97lTj/1ZCEqnqudEQkMiWvxkiXSGbdu3eLtnC/KgID+IMWXs6DzFi1aONT9i4aeKxJJXh18d1buzt/YG67beSkcU0UnX7dnnn3RYYDXQQd+xP9y6z9yPZq2/DrOJtbe4x//XrzkNSIN5w4d7t4a/aq0Zfv2bd0N3gRAQG2GYBUbTZ/1C1mVLZtTbdXriexTLllRKMBn5Gjy5E/dq6+/6dasXSv2qX7H9pFGPueC4dkqnHcN4OU4oke3ROoiaXjRx771rrhJxI9CJZxJCAmx+5w39BLv9zTXvfjs43ka/ZE6T/vVSe7YvsfkKsH/nnjGbYkzTnbq2N5d7I26SCAP+k5+qB+N6nJ4tmFcX3BUgzPPvkB8eZ5+4mF3xlkXeFWlgnvCS65H9+nvzrvQv3RjXs0lgWIvumj4ZfILj10GVSIYGjVq4H73m+skCvXot3/4szv15IHuOC+BEXBKpMzBAIlouPW2f7odO3e4f/nRTsr6indNgYhw4UCaOuH4/jl+hUlz+a+HezeOg8X2cZW3ZVHuvAKdE/eIR//3lO805fwoXTbhk+elwy4UgscX6NeXXpzX7bE4VFNVTylv+XLl3f/94bex67TXSyNfcXd4A/QPS5e5884e4n7/uxuFcHFvGfXqG+7qKy5zjHLm5Rqy0ksl3y9cFMtPJVRI4tWXn/eq6pfusiuudY88eJ/gEkvoDzD0E4Kk8Of/+51jI2BqwZ3g0Qfvjbm9XObre24+A1ZyU+BPzRrZgx8aRV3fHDPO9end033w4cduoFeDcep996033BuvviQjktjRIL7HHrpPbkML0fdQJcFgeTXvhPc+w5SE/eo3zbrp9zdnjRn7VlaNug2zah/QOKvf8adk+V+krNFjxmXt2LEjVg5v+My69obfZrVs21nSes9tuZc89hb+9vc75B5vW9pb0iJd951K8ve2jITv9346WccOOEnuo+4rf/45dm+jZm2y/IhSlpdi5LofeYpdCx5cNPzyrCOOPjYYFTv2v+xyr5dsYnEceMLJGnzW+XLN26uyvEonxw8/8rike/ud97Jq7tcoy7tjyLn+8R0ha9ilV0haysvmJbysyZ9MkSR+FC2rZ58BmjzLG3ElTRATr+pJnN4TS+wPPGFn1T2wSRZtFQye4IKn+R7zfgQxJCH4Ui4NXv3JOrhVx6ymLdtnecLW6Czf6bJ69u4vZfN2w1g895JHXsG7DWTtX79ZlpdaY5d5J5u17CD5kN/HEybFrnHgyTLrlNOGCL68675jZ3nykDTe30nuU2yD+7YdusTyWbVqdZa3EWUR59XRWDwHniQlj7ww4zmU7fIrrs1xT3FObrvjrizvtCvvKuX1P1BZnQ4/MuvInsfJe0beXm3OOqh5uyzvuJz1hz/9JWvoRZfGHuklTSmvH0CIxRX2IOWS1fED+rkXnvmfl5a6i7iKIZVpAYiOwy8eKqM+SAydOt7mVY9bvVfyNBFpb74lpxqSFxujSuEegMF2oP8VjQ9PeK9pJI1EwqDTT83z1zCRe4Np+AU84eTTvZ/Ld17q6ZzDy5qyIJU0CtgGMIJj04kP+DU1OPDA+OgCz3/zu/9zb7/7gfwKMiq1dGm2vUFvYgQIVeOxx58WWw8qFOHaG34no7EY/nEgPaRdG/FVO+nUIfIrr/cXZY/KNOySEa5Nq5buxuuz3VWwi1XwTq9cu8MbiPcWGjds4N+P9gUmW7RoiUgW/9/Oucd4VVxxfGrAgH/4R6UFlD9aQ5TySIO8W1FEpUBFpEqNrKmPCOGhCxQUcQOuL9CICkVrYAFXwBWU2oogsK8uUrA1dHlFkIU0seoqQY2KUYz+4fnM7vnt/OZ37++1K/szmZPs3nvnzsyd37l3zpzH9wyVFpQ+nIiEoVGBe8J/tb2yJmNkFQ1z2oxZ1mE9Y9pk+0xM6ZMnT4o52Nt+s5cNv1Q0CDBpLd8W2ugLa1dbvxGRbe4pQNN2Iv+InP7WsRqWLX82SdNiTrywdpUZNeY68ycxu7Zu3pTAjDEuCM3RJXxDjLfzOZ3M4kcesLfwI74jcImBA/pbCERDQ3roDd8BWqwS394ycS9sF3DrxpebtFncN2h8zDf8gTxjw0tEbYusaY2vFZwZwFZMYeYm1LFjR+025+MZF1aohW64GJX3QP2bZqWYMUuX/9UQvSia9Efz2KIHrc9lyOBBWf+ozVu2Wofo3NnFSeqxdoB/J9tcNPwrUaq79pXtkRfZrVtXi+V5+/CRJGH1QeNHthswOkpMQh+Hxb0XNwowsfmFa910R7BBCCGiqmtWPZtQx/02pQvuM9vEbAae8eauGgn5d7KmOf4+AKlEfygrW/GMkZU64a8hxI5DF1JnOqa9ghfffbfFvNFnMsGmzphpJ+QiiY4SFa2qrrX4LBD3+/YfspFgrR93ZILHAUi1zXPl66z5Uzxjmu1z7OirLQYNNwHj7C7vhMULHJji1bSte1woi2T9/gP2eyQwVCXCHxDoIw8usIvp8BGjrB/MbeOfV77+98hn4Be6WlwfShvFpHTNQsr79e1jHn/sYft+mB9zZt1lq38niyDkm1WlDy021bU7xSdaYgM5dTt3mb31+2TB6W3qJCAAVART7Ve9LrLt/X8HDh6SFKguScXzZNEbfukwwWP1SwgrKiD8CIZB5HoCGcHfDP1hwjjBoN2f+JbEcrLlREvzpfxb5vvE5naiAhpsXJhI3lOJ2PoAJtdL1OqLU6cSzuFcHrNafBRE1XyUvPZR/9auRAhVy+KOitOJu59L+aYN6+zqg7ByqbGx0V5ecH6LsEJITp2S6kvBB3RE/F3ZEEKBHMLfDB1sKtatSfFHuX0AmF0ikwFUeweJfPLxr3hmqV1Q1N9AfTQSomBKZBCIGWkvNUPAB4VqXT0SVt+8Zbu9nDuvxH78vxt1lQ02gKECTzR7ZguGjYkz9tqJFlh52y1F2o05SxaAdMQq/6KgzvF3lswXISxwmDtn3m32vFFtylaXWy3xlZcrBN813cyac6/gxZrG5PcJXILILUR4nsk6UrBmpQvnCz5qcKI6Tu3Jd9yauNYTsIQrV5XrZd5HUliAKrCQE3UDOIpggFzw5t+ao6yUk/bTWwIDpPJMEeQ9lowSwOaaHU0ZClqmx569moSPXpMcXlVTZ3ZIUCyK+EaImCJIed7adRWGSCvfK6h/fGcsfDpeFr58qd2EFTgjwrwIKpx2Vwny+go5ThEHaD7Eh7FHwrKE2P0ohvaXKf9Q67X1MS7do/HDJrOsR48LEo8kV5DV0CcEu29G+HWONhwzCIF/vLrVTvpXNlWkjXZpexzP/ClhqmeifEChaBHfiiAFQY/GrFFS91luDmTnzufYWwjKqLpuO/ecyBzmNbg2JhOpTBNumCQaXIPVAMaPG2s1iyckXWnMuBtsrqfbXs/Jkii+c6pE5obZjIm4TAi+t6gFEq2xLYQV41n21ONmr7hEEFSQTn4yCpSGykLHeFmkGHs+kUjtS49gH9HSBg0aoEUpRwQS+ZOfNydEDxkyyOYI4uIhdQsz/6uvT9t27nhTOspQ0G7CignBSscWKNU1tWZ68Z+tJAb6f+UVgpa+8nLx8QxIUXPjfg9pJFBrEetx/f8Q5Yqu/vnPutjfzjNIgyEi5tMHzVqYluMLIwkWFR/VHiK/DfX+5qIbDfxNF5bXfvI5oq2hGacj8hKPvl1vNCWHupgN/LkEPOJVAdr2FXMnzjRx62c6xwzF7zf+mjEJk/XCX/7C/Ht3rd1mB9+RhtnRYjEDFRvm940bwI1guvdpE5XU7NZpy3MWdXcR0ckPDEUJQZZuvPlqNQp90Of4x2tF+Pft3csMlPnq8gQMVtmacsGnfWh9duwW4mrrfj+ZrttNWDEwMDT8sRrw8tEoKmU1InH0iaXLzfryMnPN70dn+g02hQTHHyuc6wPI2LAdK+BwJDMeJLT7AsntA8zqE74M1wykzW2TpwvfvpS8uqE23I9JlW+SqP+8dNcI10yEoOwkkz2OcNpuED/cc8+vt8DCba9tiquaUznf0NmiiS0Wn6dL/xGtGygB35qbGP7kkkdt2H3n6H+51SPP///e+9Yck4i24NVOGFDcraG5kvO4wNmlAZMrDgTqP4e6uDxA48cR492xo9psq6yyC9uxw/vjqraqHDAofz7xnRzYu8eO8/m1FbIDyE/9Kjldn1FhxaqmCNioUfYXnBB/8+6ebQ6Lf4ftQLS+G2nx25Kawn2iKz4S3K9bKNdV1TVWdb5ZggkuYR5/dOKEW2TPwQ2Bj1Lid74kQMlewiN3NdP7hXiU8L6NwPHb2QUA026S5KxNueN2MW+6pWww95lkN0CnRCD7m8917NAh0sxBs2YB1BxG5UPPnj2teXTfvXO1yB51bzD8fGQruETu4D/Fl0dqDpvYAa6F70PEJELoKRG0wb/lk+bT+eV6jQbtYgHBL2mwQutEHRkrwSQSq10Xg8BEzBuCfN8nAQHGjmbDokZaz/x75iSyBNjDqmx1kyXi94+vsy0JfoExJPJ6Sf9UiyGXZyW/nVxa5lGXTHT+8iXXn+H2gZ8rX1+X20825yRXtybBWp+xUcK8qO0jLr9Mi+wRM0Ztf/cGTswejiOee75J5dYvxHMijgAhR0iEsljAkuwHBtoaWvTokljYAqhrH3nNflxRoFAmJ+adT2jdWyQFxl3MSLb+WHbg/PyLUzbYM/H665KaEeHie8U0B5iMBotvz0+KRiiRpJsrFQk05PoJ4xPNgFgcPHgoce2eMJaGhuO2qLZup83V/MtTybmaK1auMZu3bhfg7IUGgDW+I+ApflQbX5Lm87nPaMtzUrQQ/tbMF0H+yaefJpLc833OGRVWhI/dbP5cBk0qRnVtXS5NCrruyJEjzEWynYY7eRgw/oEoM1BAmklmIHV/bMQmiGg9UZFWUPvnnhtv0vi/tXv3rn5Rxmuf1/+tb8rTpCERsttvSd6hA/Q6O7qqUzvuAWwq+fSyJ1Nu79q920y/a05KeXfByy0smSeR8D5J9/wULPcm2hQI8tOnvxEz9mI7j266caJbxZTeX2Id8Zkc67/u18ci5JMaN18MHNaS/xl1P9uyyqoa85YEBMB9DZVgChFntgFqDf0EFGlrOsi2LWbMeZJMmenFx/WHOfiJpA+QQPpjJdThL2Uzuy5iu6MB4LdS04PXcOSdo6arAFqjon5oXJgIrr8lVz7wvGPHj9vcxGx9I0RZiaKy8V0c4ez/n2wmx+8ietQeRMQJIg0oWyLxmhQm3kU630+6/thyh3y3qGgl/MY9gZnu46HS9flD3sOU5VvzzWR9JnwEUEricxQRZcUsz3ceR/WZbdkZE1bZDijUCxwIHAgciOLAWVGFoSxwIHAgcKDQOBCEVaG9kTCewIHAgUgOBGEVyZZQGDgQOFBoHAjCqtDeSBhP4EDgQCQHgrCKZEsoDBwIHCg0DgRhVWhvJIwncCBwIJIDQVhFsiUUBg4EDhQaB4KwKrQ3EsYTOBA4EMmBIKwi2RIKAwcCBwqNA0FYFdobCeMJHAgciOTA9+a9+dSKZRFxAAAAAElFTkSuQmCC"
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## RNN基本结构\n",
    "\n",
    "![图片.png](attachment:3fadf6f8-46d7-4968-a10b-c3f4d28324c5.png)\n",
    "\n",
    "- x:输入\n",
    "- U:输入到隐含层的权重矩阵\n",
    "- W:状态到隐含层的权重矩阵\n",
    "- s:为状态\n",
    "- V:隐含层到输出层的权重矩阵\n",
    "\n",
    "![典型的Elman循环神经网络](attachment:9fb471ef-f350-47f7-b772-269bcade05c3.png)\n",
    "\n",
    "典型的Elman循环神经网络：各个时间节点对应的W、U、V都是不变的，实现参数共享，同时大大降低参数量。\n",
    "\n",
    "循环神网络的反向传播训练算法称为随时间反向传播（Backpropagation Through Time，BPTT）算法，其基本原理和反向传播算法是一样的。只不过，反向传播算法是按照层进行反向传播，而BPTT是按照时间t进行反向传播。\n",
    "\n",
    "\n",
    "梯度的消失使得我们难以知道参数朝哪个方向移动能改进代价函数，而梯度的爆炸会使学习过程变得不稳定。\n",
    "> 前边的例子中，应当都是梯度消失。\n",
    "\n",
    "RNN的梯度消失或爆炸更为明显。由于简单RNN遇到时间步（timestep）较大时，容易出现梯度消失或爆炸问题，且随着层数的增加，网络最终无法训练，无法实现长时记忆。这就导致RNN存在短时记忆问题\n",
    "\n",
    "1. 选取更好的激活函数，如ReLU激活函数。ReLU函数的左侧导数为0，右侧导数恒为1，这就避免了“梯度消失“的发生。\n",
    "2. 加入BN层，其优点包括可加速收敛、控制过拟合。\n",
    "3. 修改网络结构，LSTM结构可以有效地解决这个问题。"
   ]
  },
  {
   "attachments": {
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"
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"
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### LSTM\n",
    "长短时记忆网络（Long Short-Term Memory,LSTM），还有基于LSTM的几种变种算法，如GRU（Gated Recurrent Unit）算法等.\n",
    "\n",
    "LSTM用两个门来控制单元状态c的内容，\n",
    "1. 一个是遗忘门（Forget Gate），它决定了上一时刻的单元状态ct-1有多少保留到当前时刻$c_t$；\n",
    "2. 另一个是输入门（Input Gate），它决定了当前时刻网络的输入xt有多少保存到单元状态$c_t$。\n",
    "3. LSTM用输出门（Output Gate）来控制单元状态ct有多少输出到LSTM的当前输出值$h_t$。\n",
    "\n",
    "![image.png](attachment:7beb7a92-c986-4359-9a61-db11d1e6e6fb.png)\n",
    "\n",
    "### GRU\n",
    "GRU(Gated Recurrent Unit)，GRU对LSTM做了很多简化，比LSTM少一个Gate，因此，计算效率更高，占用内存也相对较少。\n",
    "\n",
    "GRU对LSTM做了两个大改动：\n",
    "1. 将输入门、遗忘门、输出门变为两个门：更新门（UpdateGate）zt和重置门（Reset Gate）$r_t$\n",
    "2. 将单元状态与输出合并为一个状态：$h_t$\n",
    "\n",
    "![image.png](attachment:2527a166-2c36-4034-850f-c35c57be9e9d.png)\n",
    "\n",
    "\n",
    "### Bi-RNN\n",
    "双向循环神经网络（Bidirectional Recurrent Neural Networks，Bi-RNN）: 双向循环神经网络的基本思想是提出每一个训练序列向前和向后分别是两个循环神经网络（RNN），而且这两个都连接着一个输出层。这个结构提供给输出层输入序列中每一个点完整的过去和未来的上下文信息。\n",
    "\n",
    "![image.png](attachment:8b8190f9-1d51-48b0-8dfc-a5467a2099b3.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RNN实现\n",
    "\n",
    "PyTorch提供了两个版本的API\n",
    "- 单元版的有：nn.RNNCell、nn.LSTMCell、nn.GRUCell等。输入是每个时间步，或循环神经网络的一个循环\n",
    "- 封装版的有：nn.RNN、nn.LSTM、nn.GRU。输入是一个序列\n",
    "\n",
    "\n",
    "```python\n",
    "torch.nn.RNN( args, *kwargs )\n",
    "```\n",
    "\n",
    "- input_size: 输入x的特征数量\n",
    "- hidden_size: 隐含层的特征数量\n",
    "- num_layers: RNN的层数\n",
    "- nonlinearity: 指定非线性函数使用tanh还是relu。默认tanh\n",
    "- bias: bool, false -> RNN层不会使用偏置权重$b_i$和$b_h$。默认为True\n",
    "- batch_first: bool, True -> Tensor的shape应该是（batch,seq,feature）。默认是（seq,batch,feature）序列长度，批次大小和特征维度\n",
    "- dropout: 0~1，如果非零，除最后一层外，其它层的输出都会加上一个dropout层\n",
    "- bidirectional: True, 变成双向RNN。默认为False\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "    第一层相关权重参数\n",
      "    wih形状(input) torch.Size([20, 10])\n",
      "    whh形状(hidden) torch.Size([20, 20])\n",
      "    bih形状(bias) torch.Size([20])\n",
      "    \n",
      "\n",
      "    第二层相关权重参数\n",
      "    wih形状(input) torch.Size([20, 20])\n",
      "    whh形状(hidden) torch.Size([20, 20])\n",
      "    bih形状(bias) torch.Size([20])\n",
      "    \n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "rnn = nn.RNN(input_size=10, hidden_size=20, num_layers = 2)\n",
    "\n",
    "# l0是L0，不是10\n",
    "print(\n",
    "    f\"\"\"\n",
    "    第一层相关权重参数\n",
    "    wih形状(input) {rnn.weight_ih_l0.shape}\n",
    "    whh形状(hidden) {rnn.weight_hh_l0.shape}\n",
    "    bih形状(bias) {rnn.bias_hh_l0.shape}\n",
    "    \"\"\"\n",
    ")\n",
    "\n",
    "print(\n",
    "    f\"\"\"\n",
    "    第二层相关权重参数\n",
    "    wih形状(input) {rnn.weight_ih_l1.shape}\n",
    "    whh形状(hidden) {rnn.weight_hh_l1.shape}\n",
    "    bih形状(bias) {rnn.bias_hh_l1.shape}\n",
    "    \"\"\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([100, 32, 20]) torch.Size([2, 32, 20])\n"
     ]
    }
   ],
   "source": [
    "input_= torch.randn(100, 32, 10)  # 特征长度100，批次大小32，特征维度为10\n",
    "h_0 = torch.randn(2, 32, 20)  # hidden层形状为2，32， 20\n",
    "\n",
    "output, h_n = rnn(input_, h_0)\n",
    "print(output.shape, h_n.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch.nn as nn\n",
    "\n",
    "## 基础RNN网路\n",
    "class RNN(nn.Module):\n",
    "    def __init__(self, input_size, hidden_size, output_size):\n",
    "        super(RNN, self).__init__()\n",
    "        \n",
    "        self.hidden_size = hidden_size\n",
    "        self.i2h = nn.Linear(input_size + hidden_size, hidden_size)\n",
    "        self.i2o = nn.Linear(input_size + hidden_size, output_size)\n",
    "        \n",
    "        self.softmax = nn.LogSoftmax(dim=1)\n",
    "        \n",
    "    def forward(self, input, hidden):\n",
    "        combined = torch.cat((input, hidden), 1)\n",
    "        hidden = self.i2h(combined)\n",
    "        output = self.i2o(combined)\n",
    "        output = self.softmax(output)\n",
    "        return output, hidden\n",
    "    \n",
    "    def initHidden(self):\n",
    "        return torch.zeros(1, self.hidden_size)\n",
    "    \n",
    "n_hidden = 128\n",
    "rnn = RNN(n_letters, n_hidden, n_categories)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### LSTM实现\n",
    "\n",
    "```python\n",
    "lstm = nn.LSTM(input_size=10, hidden_size=20, num_layers=2)\n",
    "```\n",
    "\n",
    "LSTM比标准的RNN多了3个线性变换，多出的3个线性变换的权重合在一起是RNN的4倍，偏移量也是RNN的4倍。所以，LSTM的参数个数是RNN的4倍。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "\n",
    "\n",
    "class LSTMCell(nn.Module):\n",
    "    def  __init__(self, input_size, hidden_size, cell_size, output_size):\n",
    "        super(LSTMCell, self).__init__()\n",
    "        self.hidden_size = hidden_size\n",
    "        self.cell_size = cell_size\n",
    "        self.gate = nn.Linear(input_size + hidden_size, cell_size)\n",
    "        self.output = nn.Linear(hidden_size, output_size)\n",
    "        self.sigmoid = nn.Sigmoid()\n",
    "        self.tanh = nn.Tanh()\n",
    "        self.softmax = nn.LogSoftmax(dim=1)\n",
    "        \n",
    "    def forward(self, input, hidden, cell):\n",
    "        combined = torch.cat((input, hidden), 1)\n",
    "        \n",
    "        f_gate = self.sigmoid(self.gate(combined))\n",
    "        i_gate = self.sigmoid(self.gate(combined))\n",
    "        o_gate = self.sigmoid(self.gate(combined))\n",
    "        z_state = self.tanh(self.gate(combined))\n",
    "        \n",
    "        cell = torch.add(torch.mul(cell, f_gate), torch.mul(z_state, i_gate))\n",
    "        hidden = torch.mul(self.tanh(cell), o_gate)\n",
    "        \n",
    "        output = self.output(hidden)\n",
    "        output = self.softmax(output)\n",
    "        \n",
    "        return output, hidden, cell\n",
    "    \n",
    "    def initHidden(self):\n",
    "        return torch.zeros(1, self.hidden_size)\n",
    "    \n",
    "    def initCell(self):\n",
    "        return torch.zeros(1, self.cell_size)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### GRU实现"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class GRUCell(nn.Module):\n",
    "    def  __init__(self, input_size, hidden_size, cell_size, output_size):\n",
    "        super(GRUCell, self).__init__()\n",
    "        self.hidden_size = hidden_size\n",
    "        self.cell_size = cell_size\n",
    "        self.gate = nn.Linear(input_size + hidden_size, cell_size)\n",
    "        self.output = nn.Linear(hidden_size, output_size)\n",
    "        self.sigmoid = nn.Sigmoid()\n",
    "        self.tanh = nn.Tanh()\n",
    "        self.softmax = nn.LogSoftmax(dim=1)\n",
    "        \n",
    "    def forward(self, input, hidden, cell):\n",
    "        combined = torch.cat((input, hidden), 1)\n",
    "        \n",
    "        z_gate = self.sigmoid(self.gate(combined))\n",
    "        r_gate = self.sigmoid(self.gate(combined))\n",
    "        \n",
    "        combined01 = torch.cat((input, torch.mul(hidden, r_gate)), 1)\n",
    "        \n",
    "        h1_state = self.tanh(self.gate(combined))\n",
    "        h_state = torch.add(torch.mul((1 - z_gate), f_gate), torch.mul(h_stage, z_gate))\n",
    "                \n",
    "        output = self.output(h_stage)\n",
    "        output = self.softmax(output)\n",
    "        \n",
    "        return output, h_state\n",
    "    \n",
    "    def initHidden(self):\n",
    "        return torch.zeros(1, self.hidden_size)"
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 文本数据处理\n",
    "\n",
    "对字典D中的任意词w，指定一个固定长度的实值向量：v(w)∈Rm,v(w)就称为w的词向量，m为词量的长度。\n",
    "\n",
    "![image.png](attachment:3ef63a95-66ca-4788-bd73-c85c0cec2efa.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "## 收集数据\n",
    "\n",
    "import jieba\n",
    "raw_text = \"\"\"我爱上海\n",
    "              她爱北京\"\"\"\n",
    "\n",
    "stoplist = [\" \", \"\\n\"] # 定义停用词"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Building prefix dict from the default dictionary ...\n",
      "Dumping model to file cache /tmp/jieba.cache\n",
      "Loading model cost 1.945 seconds.\n",
      "Prefix dict has been built successfully.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['我', '爱', '上海', '她', '爱', '北京']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 利用结巴分词\n",
    "\n",
    "words = list(jieba.cut(raw_text))\n",
    "\n",
    "words = [i for i in words if i not in stoplist]\n",
    "\n",
    "words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: '爱', 1: '北京', 2: '上海', 3: '她', 4: '我'}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 去重，并且对每个词加上索引或给一个整数\n",
    "\n",
    "word_to_ix = {i: word for i, word in enumerate(set(words))}\n",
    "\n",
    "word_to_ix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[tensor([-1.0472,  0.8495, -0.6490,  1.2202,  0.8743, -0.8300, -0.6244,  0.3225]),\n",
       " tensor([ 1.5873,  0.4626, -1.1413,  0.0873, -0.9741, -1.4892,  0.9704,  0.5417]),\n",
       " tensor([-0.3176,  0.1972, -0.4132, -0.2283, -0.0772,  0.1849,  1.1282, -0.0818]),\n",
       " tensor([ 0.3439, -2.1235,  1.3351,  0.1992,  1.6700, -0.2341,  0.8726,  0.2016]),\n",
       " tensor([-0.8794, -0.1714, -0.0799,  0.8142, -0.6639,  0.9664,  1.8371,  0.9555])]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 利用PyTorch的nn.Embedding将整数转换为向量\n",
    "from torch import nn\n",
    "import torch\n",
    "\n",
    "embeds = nn.Embedding(6, 8) # 词总数，向量长度\n",
    "lists = []\n",
    "for  k, v in word_to_ix.items():\n",
    "    tensor_value = torch.tensor(k)\n",
    "    lists.append((embeds(tensor_value).data))\n",
    "\n",
    "lists"
   ]
  },
  {
   "attachments": {
    "5fd2e3cf-01a0-44d1-adc6-c79655766a81.png": {
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"
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"
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 词嵌入\n",
    "\n",
    "我们如果要把语句或文档让机器认识出，首先需要把这些语句或文档转换成数字，其中最基本的一项任务就是把字或词转换为词向量，这个任务又被称为词嵌入。把字或词转换为向量，最开始采用One-Hot编码，用于判断文本中是否具有该词语。后来发展使用Bag-of-Words，使用词频信息对词语进行表示。再后来使用TF-IDF根据词语在文本中分布情况进行表示。而近年来，随着神经网络的发展，分布式的词语表达得到大量使用，Word2Vec就是对词语进行连续的多维向量表示。\n",
    "\n",
    "### 独热表示 one-hot\n",
    "独热表示的向量长度为词典的大小，向量的分量只有一个1，其他全为0，1的位置对应该词在词典中的位置\n",
    "\n",
    "![image.png](attachment:b867f53c-d8c6-4ae8-85ba-5fe38c932de0.png)\n",
    "\n",
    "对字或词转换为独热向量，而整篇文章则转换为一个稀疏矩阵。\n",
    "\n",
    "\n",
    "### 词袋模型 Bag-of-words\n",
    "在one-hot基础上发展而来，将整篇文章中的词按照词频构建衣蛾大胆的稀疏矩阵\n",
    "\n",
    "1. 容易受维数灾难的困扰，尤其是将其用于深度学习算法时；\n",
    "2. 任何两个词都是孤立的，存在语义鸿沟词（任意两个词之间都是孤立的，不能体现词和词之间的关系）。为了克服此不足，人们提出了另一种表示方法，即分布式表示。\n",
    "\n",
    "\n",
    "### 分布式表示\n",
    "解决词汇与位置无关问题，可以通过计算向量之间的距离（欧式距离、余弦距离等）来体现词与词的相似性。\n",
    "\n",
    "词向量的分布式表示的优点是解决了词汇与位置无关问题，不足是学习过程相对复杂且受训练语料的影响很大。\n",
    "\n",
    "训练这种向量表示的方法较多，常见的有LSA、PLSA、LDA、Word2Vec等\n",
    "\n",
    "- Word2Vec\n",
    "    - 根据上下文生成目标值（即方法1）使用CBOW模型。对于每一个词汇（Word），使用该词汇周围的词汇来预测当前词汇生成的概率。\n",
    "        - CBOW模型包含3层，即输入层、映射层和输出层。\n",
    "        ![image.png](attachment:5fd2e3cf-01a0-44d1-adc6-c79655766a81.png)\n",
    "    - 根据目标值生成上下文（即方法2）采用Skip-Gram模型。对于每一个词汇，使用该词汇本身来预测生成其他词汇的概率。\n",
    "        - Skip-Gram模型同样包含3层，输入层，映射层和输出层。\n",
    "        ![image.png](attachment:ad880eeb-a78a-419c-8e35-749c1b0048ee.png)\n",
    "        \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 词性预测\n",
    "\n",
    "1. 实现词的向量化。假设有两个句子，作为训练数据，这两个句子的每个单词都已标好词性。当然我们不能直接把这两个语句直接输入LSTM模型，输入前需要把每个语句的单词向量化。假设这个句子共有5个单词，通过单词向量化后，就可得到序列[V1,V2,V3,V4,V5]，其中Vi表示第i个单词对应的向量。如何实现词的向量化？我们可以直接利用nn.Embedding层。当然在使用该层之前，需要把每句话对应单词或词性用整数表示。\n",
    "\n",
    "2. 构建网络。词向量化之后，需要构建一个网络来训练，可以构建一个只有3层的网络，第一层为词嵌入层，第二层为LSTM层，最后一层用于词性分类的全连接层。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'The': 0, 'cat': 1, 'ate': 2, 'the': 3, 'fish': 4, 'They': 5, 'read': 6, 'that': 7, 'book': 8}\n",
      "{'DET': 0, 'NN': 1, 'V': 2}\n"
     ]
    }
   ],
   "source": [
    "training_data = [\n",
    "    (\n",
    "        \"The cat ate the fish\".split(),\n",
    "        [\"DET\",  \"NN\", \"V\", \"DET\", \"NN\"]\n",
    "    ),\n",
    "    (\n",
    "        \"They read that book\".split(),\n",
    "        [\"NN\", \"V\", \"DET\", \"NN\"]\n",
    "    )\n",
    "]\n",
    "\n",
    "testing_data = [(\"They ate the fish\").split()]\n",
    "\n",
    "\n",
    "# 构建索引\n",
    "word_to_ix, tag_to_ix = {}, {}\n",
    "for sent, tags in training_data:\n",
    "    for i in range(len(sent)):\n",
    "        word = sent[i]\n",
    "        tag = tags[i]\n",
    "        word_to_ix[word] = word_to_ix.get(word, len(word_to_ix))\n",
    "        tag_to_ix[tag] = tag_to_ix.get(tag, len(tag_to_ix))\n",
    "print(word_to_ix)\n",
    "print(tag_to_ix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 构建网络\n",
    "import torch\n",
    "\n",
    "from torch import nn\n",
    "import torch.nn.functional as F\n",
    "\n",
    "\n",
    "class LSTMTagger(nn.Module):\n",
    "    def  __init__(self, embedding_dim, hidden_dim, vocab_size, tagset_size):\n",
    "        super(LSTMTagger, self).__init__()\n",
    "        self.hidden_dim = hidden_dim\n",
    "        self.word_embeddings = nn.Embedding(vocab_size, embedding_dim)\n",
    "        \n",
    "        self.lstm = nn.LSTM(embedding_dim, hidden_dim)\n",
    "        \n",
    "        self.hidden2tag = nn.Linear(hidden_dim, tagset_size)\n",
    "        self.hidden = self.init_hidden()\n",
    "        \n",
    "    def init_hidden(self):\n",
    "        return (\n",
    "            torch.zeros(1, 1, self.hidden_dim),\n",
    "            torch.zeros(1, 1, self.hidden_dim)\n",
    "        )\n",
    "        \n",
    "    def forward(self, sentence):\n",
    "        # 获得词嵌入矩阵\n",
    "        embeds = self.word_embeddings(sentence)\n",
    "        \n",
    "        # 按lstm格式修改embeds形状\n",
    "        lstm_out, self.hidden =  self.lstm(\n",
    "            embeds.view(len(sentence), 1, -1),\n",
    "            self.hidden\n",
    "        )\n",
    "    \n",
    "        # 修改隐含状态形状，作为全连接层的输入\n",
    "        tag_space = self.hidden2tag(lstm_out.view(len(sentence), -1))\n",
    "    \n",
    "        # 计算每个单词属于各词性的概率\n",
    "        tag_scores = F.log_softmax(tag_space, dim=1)\n",
    "        return tag_scores\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "EMBEDDING_DIM = 10\n",
    "HIDDEN_DIM = 3\n",
    "\n",
    "model = LSTMTagger(EMBEDDING_DIM, HIDDEN_DIM, len(word_to_ix), len(tag_to_ix))\n",
    "\n",
    "loss = nn.NLLLoss()\n",
    "\n",
    "optimizer = torch.optim.SGD(model.parameters(), lr=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['The', 'cat', 'ate', 'the', 'fish']\n",
      "tensor([0, 1, 2, 3, 4])\n",
      "tensor([[-1.2506, -1.2136, -0.8758],\n",
      "        [-1.2203, -1.2123, -0.8981],\n",
      "        [-1.3024, -1.0470, -0.9752],\n",
      "        [-1.2652, -0.9538, -1.1009],\n",
      "        [-1.2633, -0.9638, -1.0912]], grad_fn=<LogSoftmaxBackward>)\n",
      "torch.return_types.max(\n",
      "values=tensor([-0.8758, -0.8981, -0.9752, -0.9538, -0.9638], grad_fn=<MaxBackward0>),\n",
      "indices=tensor([2, 2, 2, 1, 1]))\n"
     ]
    }
   ],
   "source": [
    "def prepare_sequence(seq, to_ix):\n",
    "    idxs = [to_ix[w] for w in seq]\n",
    "    tensor =  torch.LongTensor(idxs)\n",
    "    return tensor\n",
    "\n",
    "\n",
    "inputs = prepare_sequence(training_data[0][0], word_to_ix)\n",
    "print(training_data[0][0])\n",
    "print(inputs)\n",
    "\n",
    "tag_scores = model(inputs)\n",
    "\n",
    "print(tag_scores)\n",
    "print(torch.max(tag_scores, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['The', 'cat', 'ate', 'the', 'fish']\n",
      "tensor([0, 1, 2, 3, 4])\n",
      "tensor([[-0.0877, -2.5735, -4.8688],\n",
      "        [-2.4738, -0.0892, -6.7942],\n",
      "        [-3.3615, -4.3702, -0.0485],\n",
      "        [-0.1074, -3.0848, -2.8813],\n",
      "        [-4.1538, -0.0275, -4.4730]], grad_fn=<LogSoftmaxBackward>)\n",
      "torch.return_types.max(\n",
      "values=tensor([-0.0877, -0.0892, -0.0485, -0.1074, -0.0275], grad_fn=<MaxBackward0>),\n",
      "indices=tensor([0, 1, 2, 0, 1]))\n"
     ]
    }
   ],
   "source": [
    "# 加大力度\n",
    "for epoch in range(400):\n",
    "    for sentence, tags in training_data:\n",
    "        model.zero_grad()\n",
    "        \n",
    "        model.hidden = model.init_hidden()\n",
    "        sentence_in = prepare_sequence(sentence, word_to_ix)\n",
    "        targets = prepare_sequence(tags, tag_to_ix)\n",
    "        \n",
    "        tag_scores = model(sentence_in)\n",
    "        \n",
    "        l = loss(tag_scores, targets)\n",
    "        l.backward()\n",
    "        optimizer.step()\n",
    "        \n",
    "inputs = prepare_sequence(training_data[0][0], word_to_ix)\n",
    "print(training_data[0][0])\n",
    "print(inputs)\n",
    "\n",
    "tag_scores = model(inputs)\n",
    "\n",
    "print(tag_scores)\n",
    "print(torch.max(tag_scores, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['They', 'ate', 'the', 'fish']\n",
      "tensor([5, 2, 3, 4])\n",
      "tensor([[-6.1456e+00, -3.7958e-03, -6.4096e+00],\n",
      "        [-4.0477e+00, -4.2293e+00, -3.2548e-02],\n",
      "        [-1.2864e-01, -2.9261e+00, -2.7015e+00],\n",
      "        [-4.3811e+00, -2.3700e-02, -4.5180e+00]], grad_fn=<LogSoftmaxBackward>)\n",
      "torch.return_types.max(\n",
      "values=tensor([-0.0038, -0.0325, -0.1286, -0.0237], grad_fn=<MaxBackward0>),\n",
      "indices=tensor([1, 2, 0, 1]))\n"
     ]
    }
   ],
   "source": [
    "inputs = prepare_sequence(testing_data[0], word_to_ix)\n",
    "print(testing_data[0])\n",
    "print(inputs)\n",
    "\n",
    "tag_scores = model(inputs)\n",
    "\n",
    "print(tag_scores)\n",
    "print(torch.max(tag_scores, 1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## LSTM预测股票行情\n",
    "\n",
    "这里采用沪深300指数数据，时间跨度为2010年1月1日至今，选择每天最高价格。假设当天最高价依赖当天的前n（如30）天的沪深300的最高价。用LSTM模型来捕捉最高价的时序信息，通过训练模型，使之学会用前n天的最高价，来判断当天的最高价（作为训练的标签值）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "本接口即将停止更新，请尽快使用Pro版接口：https://waditu.com/document/2\n"
     ]
    }
   ],
   "source": [
    "import tushare as ts\n",
    "\n",
    "cons = ts.get_apis()\n",
    "\n",
    "# 获取沪深指数000300的信息，包括交易日期datetime、开盘open、收盘close、最高high、最低low、成交量vol、成交金额amount、涨跌幅p_change\n",
    "df = ts.bar(\"000300\", conn = cons, asset=\"INDEX\", start_date=\"2010-01-01\", end_date=\"\")\n",
    "\n",
    "df = df.dropna()\n",
    "\n",
    "df.to_csv(\"sh300.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['code', 'open', 'close', 'high', 'low', 'vol', 'amount', 'p_change'], dtype='object')\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>p_change</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2643.000000</td>\n",
       "      <td>2643.000000</td>\n",
       "      <td>2643.000000</td>\n",
       "      <td>2643.000000</td>\n",
       "      <td>2.643000e+03</td>\n",
       "      <td>2.643000e+03</td>\n",
       "      <td>2643.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3235.501767</td>\n",
       "      <td>3238.321150</td>\n",
       "      <td>3263.430711</td>\n",
       "      <td>3208.450151</td>\n",
       "      <td>1.119664e+06</td>\n",
       "      <td>1.399520e+11</td>\n",
       "      <td>0.023261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>694.563958</td>\n",
       "      <td>694.913195</td>\n",
       "      <td>700.724090</td>\n",
       "      <td>686.319360</td>\n",
       "      <td>8.907617e+05</td>\n",
       "      <td>1.258917e+11</td>\n",
       "      <td>1.459508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2079.870000</td>\n",
       "      <td>2086.970000</td>\n",
       "      <td>2118.790000</td>\n",
       "      <td>2023.170000</td>\n",
       "      <td>2.190120e+05</td>\n",
       "      <td>2.120044e+10</td>\n",
       "      <td>-8.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2597.075000</td>\n",
       "      <td>2596.750000</td>\n",
       "      <td>2617.795000</td>\n",
       "      <td>2575.900000</td>\n",
       "      <td>5.969135e+05</td>\n",
       "      <td>6.434575e+10</td>\n",
       "      <td>-0.640000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3245.740000</td>\n",
       "      <td>3249.440000</td>\n",
       "      <td>3270.900000</td>\n",
       "      <td>3220.280000</td>\n",
       "      <td>8.602910e+05</td>\n",
       "      <td>1.026381e+11</td>\n",
       "      <td>0.030000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3760.680000</td>\n",
       "      <td>3764.655000</td>\n",
       "      <td>3792.980000</td>\n",
       "      <td>3735.450000</td>\n",
       "      <td>1.262932e+06</td>\n",
       "      <td>1.604306e+11</td>\n",
       "      <td>0.710000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5379.470000</td>\n",
       "      <td>5353.750000</td>\n",
       "      <td>5380.430000</td>\n",
       "      <td>5283.090000</td>\n",
       "      <td>6.864391e+06</td>\n",
       "      <td>9.494980e+11</td>\n",
       "      <td>6.710000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              open        close         high          low           vol  \\\n",
       "count  2643.000000  2643.000000  2643.000000  2643.000000  2.643000e+03   \n",
       "mean   3235.501767  3238.321150  3263.430711  3208.450151  1.119664e+06   \n",
       "std     694.563958   694.913195   700.724090   686.319360  8.907617e+05   \n",
       "min    2079.870000  2086.970000  2118.790000  2023.170000  2.190120e+05   \n",
       "25%    2597.075000  2596.750000  2617.795000  2575.900000  5.969135e+05   \n",
       "50%    3245.740000  3249.440000  3270.900000  3220.280000  8.602910e+05   \n",
       "75%    3760.680000  3764.655000  3792.980000  3735.450000  1.262932e+06   \n",
       "max    5379.470000  5353.750000  5380.430000  5283.090000  6.864391e+06   \n",
       "\n",
       "             amount     p_change  \n",
       "count  2.643000e+03  2643.000000  \n",
       "mean   1.399520e+11     0.023261  \n",
       "std    1.258917e+11     1.459508  \n",
       "min    2.120044e+10    -8.750000  \n",
       "25%    6.434575e+10    -0.640000  \n",
       "50%    1.026381e+11     0.030000  \n",
       "75%    1.604306e+11     0.710000  \n",
       "max    9.494980e+11     6.710000  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(df.columns)\n",
    "\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>code</th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>p_change</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-11-19</th>\n",
       "      <td>000300</td>\n",
       "      <td>4880.92</td>\n",
       "      <td>4927.99</td>\n",
       "      <td>4939.79</td>\n",
       "      <td>4870.20</td>\n",
       "      <td>1336813.0</td>\n",
       "      <td>2.477271e+11</td>\n",
       "      <td>0.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-18</th>\n",
       "      <td>000300</td>\n",
       "      <td>4889.67</td>\n",
       "      <td>4891.67</td>\n",
       "      <td>4911.09</td>\n",
       "      <td>4870.72</td>\n",
       "      <td>1642166.0</td>\n",
       "      <td>2.907272e+11</td>\n",
       "      <td>-0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-17</th>\n",
       "      <td>000300</td>\n",
       "      <td>4903.12</td>\n",
       "      <td>4894.79</td>\n",
       "      <td>4909.29</td>\n",
       "      <td>4865.39</td>\n",
       "      <td>1514874.0</td>\n",
       "      <td>2.889114e+11</td>\n",
       "      <td>-0.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-16</th>\n",
       "      <td>000300</td>\n",
       "      <td>4880.96</td>\n",
       "      <td>4904.17</td>\n",
       "      <td>4904.17</td>\n",
       "      <td>4848.62</td>\n",
       "      <td>1487709.0</td>\n",
       "      <td>2.667050e+11</td>\n",
       "      <td>0.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-13</th>\n",
       "      <td>000300</td>\n",
       "      <td>4886.98</td>\n",
       "      <td>4856.85</td>\n",
       "      <td>4886.98</td>\n",
       "      <td>4825.76</td>\n",
       "      <td>1336930.0</td>\n",
       "      <td>2.553531e+11</td>\n",
       "      <td>-1.05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              code     open    close     high      low        vol  \\\n",
       "datetime                                                            \n",
       "2020-11-19  000300  4880.92  4927.99  4939.79  4870.20  1336813.0   \n",
       "2020-11-18  000300  4889.67  4891.67  4911.09  4870.72  1642166.0   \n",
       "2020-11-17  000300  4903.12  4894.79  4909.29  4865.39  1514874.0   \n",
       "2020-11-16  000300  4880.96  4904.17  4904.17  4848.62  1487709.0   \n",
       "2020-11-13  000300  4886.98  4856.85  4886.98  4825.76  1336930.0   \n",
       "\n",
       "                  amount  p_change  \n",
       "datetime                            \n",
       "2020-11-19  2.477271e+11      0.74  \n",
       "2020-11-18  2.907272e+11     -0.06  \n",
       "2020-11-17  2.889114e+11     -0.19  \n",
       "2020-11-16  2.667050e+11      0.97  \n",
       "2020-11-13  2.553531e+11     -1.05  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f420303f640>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 可视化最高价\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "plt.plot(df[\"high\"], label=\"real-data\")\n",
    "plt.legend(loc=\"upper right\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 预处理数据\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "import pandas as pd\n",
    "\n",
    "\n",
    "def generate_data_by_n_days(series, n, index=False):\n",
    "    u\"\"\"\n",
    "    生成训练数据\n",
    "    通过一个序列来生成一个31*(count(*)-train_end)矩阵（用于处理时序的数据）\n",
    "    其中最后一列维标签数据。就是把当天的前n天作为参数，当天的数据作为label\n",
    "    \"\"\"\n",
    "    if len(series) <= n:\n",
    "        raise Exception(f\"The length of series is {len(series)}, while affect by (n={n})\")\n",
    "        \n",
    "    df = pd.DataFrame()\n",
    "    for i in range(n):\n",
    "        df[f\"c{i}\"] = series.tolist()[i:-(n - i)]\n",
    "    df[\"y\"] = series.tolist()[n:]\n",
    "    \n",
    "    if index:\n",
    "        df.index = series.index[n:]\n",
    "    return df\n",
    "\n",
    "\n",
    "def readData(df, column=\"high\", n=30, all_too=True, index=False, train_end=-500):\n",
    "    u\"\"\"\n",
    "    参数n与上相同\n",
    "    train_end表示后边多少个数据作为测试集\n",
    "    \"\"\"\n",
    "    # 以日期为索引\n",
    "    df.index = list(map(lambda x: datetime.datetime.strptime(x, \"%Y-%m-%d\"), df.index))\n",
    "    print(df.index)\n",
    "    # 获取每天的最高价\n",
    "    df_column = df[column].copy()\n",
    "    \n",
    "    # 拆分为训练集和测试集\n",
    "    df_column_train, df_column_test = df_column[:train_end], df_column[train_end - n:]\n",
    "    \n",
    "    # 生成训练数据\n",
    "    df_generate_train = generate_data_by_n_days(df_column_train, n, index=index)\n",
    "    \n",
    "    if all_too:\n",
    "        return df_generate_train, df_column, df.index.tolist()\n",
    "    \n",
    "    return df_generate_train\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch import nn\n",
    "from torch.utils.data import Dataset, DataLoader\n",
    "\n",
    "# 构建网络\n",
    "class RNN(nn.Module):\n",
    "    def __init__(self, input_size):\n",
    "        super(RNN, self).__init__()\n",
    "        self.rnn = nn.LSTM(\n",
    "            input_size=input_size,\n",
    "            hidden_size=64,\n",
    "            num_layers=1,\n",
    "            batch_first=True\n",
    "        )\n",
    "        self.out = nn.Sequential(nn.Linear(64, 1))\n",
    "        \n",
    "    def forward(self, x):\n",
    "        r_out, (h_n, h_c) = self.rnn(x, None)\n",
    "        \n",
    "        out = self.out(r_out)\n",
    "        return out\n",
    "    \n",
    "class mytrainset(Dataset):\n",
    "    def __init__(self, data):        \n",
    "        self.data, self.label = data[:, :-1].float(), data[:, -1].float()\n",
    "             \n",
    "    def __getitem__(self, index):\n",
    "        return self.data[index], self.label[index]\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.data)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "n = 30\n",
    "LR = 0.001\n",
    "EPOCH = 200\n",
    "batch_size=20\n",
    "train_end =-600"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DatetimeIndex(['2020-11-19', '2020-11-18', '2020-11-17', '2020-11-16',\n",
      "               '2020-11-13', '2020-11-12', '2020-11-11', '2020-11-10',\n",
      "               '2020-11-09', '2020-11-06',\n",
      "               ...\n",
      "               '2010-01-18', '2010-01-15', '2010-01-14', '2010-01-13',\n",
      "               '2010-01-12', '2010-01-11', '2010-01-08', '2010-01-07',\n",
      "               '2010-01-06', '2010-01-05'],\n",
      "              dtype='datetime64[ns]', length=2643, freq=None)\n"
     ]
    }
   ],
   "source": [
    "# 规范化数据\n",
    "import numpy as np\n",
    "import torch\n",
    "from torch.utils.data import DataLoader\n",
    "\n",
    "\n",
    "df = pd.read_csv(\"sh300.csv\", index_col=0)\n",
    "df, df_all, df_index = readData(df, \"high\", n=n, train_end=train_end)\n",
    "\n",
    "df_numpy = np.array(df)\n",
    "df_numpy_mean = np.mean(df_numpy)\n",
    "df_numpy_std = np.std(df_numpy)\n",
    "df_numpy = (df_numpy - df_numpy_mean) / df_numpy_std\n",
    "\n",
    "df_tensor = torch.Tensor(df_numpy)\n",
    "trainset = mytrainset(df_tensor)\n",
    "trainloader = DataLoader(trainset, batch_size=batch_size, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "           c0       c1       c2       c3       c4       c5       c6       c7  \\\n",
      "0     4939.79  4911.09  4909.29  4904.17  4886.98  4926.34  4957.58  4995.41   \n",
      "1     4911.09  4909.29  4904.17  4886.98  4926.34  4957.58  4995.41  4997.80   \n",
      "2     4909.29  4904.17  4886.98  4926.34  4957.58  4995.41  4997.80  4897.63   \n",
      "3     4904.17  4886.98  4926.34  4957.58  4995.41  4997.80  4897.63  4885.11   \n",
      "4     4886.98  4926.34  4957.58  4995.41  4997.80  4897.63  4885.11  4825.46   \n",
      "...       ...      ...      ...      ...      ...      ...      ...      ...   \n",
      "2008  2350.02  2357.85  2394.50  2413.42  2412.14  2405.18  2390.78  2388.36   \n",
      "2009  2357.85  2394.50  2413.42  2412.14  2405.18  2390.78  2388.36  2354.16   \n",
      "2010  2394.50  2413.42  2412.14  2405.18  2390.78  2388.36  2354.16  2358.56   \n",
      "2011  2413.42  2412.14  2405.18  2390.78  2388.36  2354.16  2358.56  2371.12   \n",
      "2012  2412.14  2405.18  2390.78  2388.36  2354.16  2358.56  2371.12  2350.07   \n",
      "\n",
      "           c8       c9  ...      c21      c22      c23      c24      c25  \\\n",
      "0     4997.80  4897.63  ...  4801.63  4793.47  4849.61  4825.55  4833.89   \n",
      "1     4897.63  4885.11  ...  4793.47  4849.61  4825.55  4833.89  4830.46   \n",
      "2     4885.11  4825.46  ...  4849.61  4825.55  4833.89  4830.46  4845.92   \n",
      "3     4825.46  4793.40  ...  4825.55  4833.89  4830.46  4845.92  4823.27   \n",
      "4     4793.40  4738.02  ...  4833.89  4830.46  4845.92  4823.27  4695.40   \n",
      "...       ...      ...  ...      ...      ...      ...      ...      ...   \n",
      "2008  2354.16  2358.56  ...  2421.93  2452.60  2467.99  2460.56  2427.79   \n",
      "2009  2358.56  2371.12  ...  2452.60  2467.99  2460.56  2427.79  2426.53   \n",
      "2010  2371.12  2350.07  ...  2467.99  2460.56  2427.79  2426.53  2470.21   \n",
      "2011  2350.07  2367.03  ...  2460.56  2427.79  2426.53  2470.21  2477.23   \n",
      "2012  2367.03  2364.98  ...  2427.79  2426.53  2470.21  2477.23  2450.30   \n",
      "\n",
      "          c26      c27      c28      c29        y  \n",
      "0     4830.46  4845.92  4823.27  4695.40  4634.72  \n",
      "1     4845.92  4823.27  4695.40  4634.72  4616.68  \n",
      "2     4823.27  4695.40  4634.72  4616.68  4613.63  \n",
      "3     4695.40  4634.72  4616.68  4613.63  4599.54  \n",
      "4     4634.72  4616.68  4613.63  4599.54  4631.95  \n",
      "...       ...      ...      ...      ...      ...  \n",
      "2008  2426.53  2470.21  2477.23  2450.30  2481.34  \n",
      "2009  2470.21  2477.23  2450.30  2481.34  2490.55  \n",
      "2010  2477.23  2450.30  2481.34  2490.55  2473.97  \n",
      "2011  2450.30  2481.34  2490.55  2473.97  2462.81  \n",
      "2012  2481.34  2490.55  2473.97  2462.81  2459.19  \n",
      "\n",
      "[2013 rows x 31 columns]\n",
      "[[ 2.13416831  2.09557101  2.09315027 ...  2.0079269   1.97746597\n",
      "   1.80549955]\n",
      " [ 2.09557101  2.09315027  2.08626462 ...  1.97746597  1.80549955\n",
      "   1.72389383]\n",
      " [ 2.09315027  2.08626462  2.06314659 ...  1.80549955  1.72389383\n",
      "   1.69963268]\n",
      " ...\n",
      " [-1.28887398 -1.26342935 -1.26515076 ... -1.21383115 -1.1720869\n",
      "  -1.1597008 ]\n",
      " [-1.26342935 -1.26515076 -1.27451094 ... -1.1720869  -1.1597008\n",
      "  -1.18199847]\n",
      " [-1.26515076 -1.27451094 -1.29387683 ... -1.1597008  -1.18199847\n",
      "  -1.19700703]]\n",
      "[ 1.72389383  1.69963268  1.69553087 ... -1.18199847 -1.19700703\n",
      " -1.2018754 ]\n"
     ]
    }
   ],
   "source": [
    "print(df)\n",
    "print(df_numpy[:, :-1])\n",
    "print(df_numpy[:, -1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "step: 184; loss: 0.0068889702670276165\n",
      "step: 185; loss: 0.006770038977265358\n",
      "step: 186; loss: 0.006724815350025892\n",
      "step: 187; loss: 0.006729811895638704\n",
      "step: 188; loss: 0.006732421461492777\n",
      "step: 189; loss: 0.006712169386446476\n",
      "step: 190; loss: 0.006765690632164478\n",
      "step: 191; loss: 0.006685296073555946\n",
      "step: 192; loss: 0.00681697903200984\n",
      "step: 193; loss: 0.006709517445415258\n",
      "step: 194; loss: 0.006816406734287739\n",
      "step: 195; loss: 0.006867499556392431\n",
      "step: 196; loss: 0.006799616850912571\n",
      "step: 197; loss: 0.006689609494060278\n",
      "step: 198; loss: 0.0066132512874901295\n",
      "step: 199; loss: 0.006608759984374046\n"
     ]
    }
   ],
   "source": [
    "# 训练模型\n",
    "import torch\n",
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "\n",
    "rnn = RNN(n).to(device)\n",
    "optimizer = torch.optim.Adam(rnn.parameters(), lr=LR)\n",
    "\n",
    "loss_func = nn.MSELoss()\n",
    "for step in range(EPOCH):\n",
    "    for tx, ty in trainloader:\n",
    "        tx = tx.to(device)\n",
    "        ty = ty.to(device)\n",
    "        \n",
    "        output = rnn(torch.unsqueeze(tx, dim=1)).to(device)\n",
    "        loss = loss_func(torch.squeeze(output), ty)\n",
    "        \n",
    "        optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "    print(f\"step: {step}; loss: {loss}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 测试代码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "generate_data_train = []\n",
    "generate_data_test = []\n",
    "\n",
    "test_index = len(df_all) + train_end\n",
    "\n",
    "df_all_normal = (df_all - df_numpy_mean) / df_numpy_std\n",
    "df_all_normal_tensor = torch.Tensor(df_all_normal)\n",
    "for i in range(n, len(df_all)):\n",
    "    x = df_all_normal_tensor[i - n:i].to(device)\n",
    "    #rnn的输入必须是3维，故需添加两个1维的维度，最后成为[1,1,input_size]\n",
    "    x = torch.unsqueeze(torch.unsqueeze(x, dim=0), dim=0)\n",
    "    \n",
    "    y = rnn(x).to(device)\n",
    "    if i < test_index:\n",
    "        generate_data_train.append(torch.squeeze(y).detach().cpu().numpy() * df_numpy_std + df_numpy_mean)\n",
    "    else:\n",
    "        generate_data_test.append(torch.squeeze(y).detach().cpu().numpy() * df_numpy_std + df_numpy_mean)\n",
    "plt.plot(df_index[n:train_end], generate_data_train, label='generate_train')\n",
    "plt.plot(df_index[train_end:], generate_data_test, label='generate_test')\n",
    "plt.plot(df_index[train_end:], df_all[train_end:], label='real-data')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.clf()\n",
    "plt.plot(df_index[train_end:-500], df_all[train_end:-500], label='real-data')\n",
    "plt.plot(df_index[train_end:-500], generate_data_test[-600:-500], label='generate_test')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "循环神经网络RNN适合于处理序列数据，序列长度不固定。\n",
    "\n",
    "RNN使用范围广\n",
    "\n",
    "1. 没有使用RNN的Vanilla模型，从固定大小的输入得到固定大小输出（比如图像分类）。\n",
    "2. 序列输出（比如图片字幕，输入一张图片输出一段文字序列）。\n",
    "3. 序列输入（比如情感分析，输入一段文字，然后将它分类成积极或者消极情感）。\n",
    "4. 序列输入和序列输出（比如机器翻译：一个RNN读取一条英文语句，然后将它以法语形式输出）。\n",
    "5. 同步序列输入输出（比如视频分类，对视频中每一帧打标签）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
